A tree multi-branch power distribution network traveling wave fault location method and system and medium

Abstract

The application relates to the technical field of power system relay protection, in particular to a tree-shaped multi-branch power distribution network traveling wave fault positioning method and system and a medium. The modal sample entropy value of a point close to a fault point increases with the distance of the measuring point, so that the modal sample entropy value of the fault traveling wave increases, the nearest point pair with the minimum modal sample entropy value is screened out and is respectively used as a fault upstream key measuring point and a fault downstream key measuring point, and the branch number and the node number between the fault initial traveling wave position, the fault upstream key measuring point and the fault downstream key measuring point are used as criteria to further determine the fault section, so as to solve the problem of how to quickly position the fault of the power distribution network.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system relay protection, and particularly relates to a traveling wave fault positioning method and system for tree-shaped multi-branch power distribution network and a medium. BACKGROUND

[0002] At present, the proportion of hidden power transmission in urban power distribution network architecture has been significantly increased, and cable lines have gradually become an important carrier for urban power transmission, thereby forming an overhead line and cable composite power supply network. For traditional pure overhead lines, the fault characteristics of the mixed line in the overhead line and cable composite power supply network are more complex, which increases the difficulty of fault disposal in the power distribution network.

[0003] The traditional mainstream fault diagnosis method often adopts a double-end measuring point positioning method, traveling wave detection devices are installed at two ends of a line A and B, the times t1 and t2 when the traveling wave reaches the A end and the B end are recorded synchronously, and the distance between the fault point C and the A / B end can be calculated according to the known full length L of the line and the fixed traveling wave speed v of current propagation, so as to locate the exact position of the fault occurrence point.

[0004] However, as the scale of the power distribution network increases, the arrangement of the power collection line tends to be complex and the length gradually increases, multiple measuring points are required to realize fault positioning, which increases the positioning difficulty and positioning response time of the fault. In view of this, the present application proposes a new fault positioning method in the power distribution network to overcome the influence of the transition resistance and the fault distance in the complex power distribution network and realize the rapid positioning of the fault in the complex power distribution network. SUMMARY

[0005] The main purpose of the present application is to provide a traveling wave fault positioning method for tree-shaped multi-branch power distribution network, which aims to solve the problem of how to rapidly position the fault of the power distribution network.

[0006] To achieve the above-mentioned purpose, the present application provides a traveling wave fault positioning method for tree-shaped multi-branch power distribution network, which comprises the following steps:

[0007] S10, when the fault traveling wave signal in the power distribution network is acquired, the fault initial traveling wave position corresponding to the fault traveling wave signal is determined, the modal component with the maximum energy except the power frequency in the fault traveling wave signal is extracted, and the sample entropy corresponding to the modal component is calculated. The adjacent point pair with the smallest sample entropy is taken as the fault upstream key measuring point and the fault downstream key measuring point;

[0008] S20, the total number of branches and the total number of nodes between the fault upstream key measuring point and the fault downstream key measuring point are taken as criteria, and the difference between the criteria and each element in the topology information matrix is calculated, wherein the element is composed of the first branch number and the first node number between the fault initial traveling wave position and the fault upstream key measuring point;

[0009] S30, determining the section associated with the element corresponding to the minimum difference value among the differences as the fault section.

[0010] Optionally, in the S20, the expression of the criterion is:

[0011]

[0012] wherein, ;

[0013] wherein, is a decay function, is the refraction coefficient brought by the traveling wave through the branch, is the total number of branches, is the total number of nodes, is the initial voltage traveling wave amplitude of the key measuring point upstream of the fault, is the initial voltage traveling wave amplitude of the key measuring point downstream of the fault, is the refraction coefficient of the fault traveling wave at the branch.

[0014] Optionally, in the S20, the expression of the topological information matrix is:

[0015]

[0016] wherein, is an element in the matrix K, is the first branch number of the fault initial traveling wave to the key measuring point upstream of the fault, is the first node number of the fault initial traveling wave to the key measuring point downstream of the fault, is the refraction coefficient brought by the traveling wave through the branch, m is the number of cable sections, and n is the number of nodes.

[0017] Optionally, in the S20, the calculation expression of the difference between the criterion and each element in the topological information matrix includes:

[0018]

[0019] wherein, is the difference between the criterion and each element in the topological information matrix, is a topological information matrix of order m, is a full 1 matrix of the same order, is a decay function, is the refraction coefficient brought by the traveling wave through the branch, is the total number of branches, is the total number of nodes.

[0020] Optionally, before the step S30, the method further comprises:

[0021] S40, determining the size between the minimum difference value and an adaptive threshold value;

[0022] S50, if the minimum difference value is less than or equal to the adaptive threshold value, performing the step S30;

[0023] S60, otherwise, removing the element corresponding to the minimum difference value from the topological information matrix, re-computing the difference value between the criterion and each element in the updated topological information matrix, selecting the current minimum difference value from each difference value, and returning to perform the step S40 until the obtained current minimum difference value is less than or equal to the adaptive threshold value.

[0024] Optionally, the adaptive threshold value is calculated by the following expression:

[0025]

[0026] wherein, is the refraction coefficient caused by the traveling wave passing through the branch, .

[0027] Optionally, in the S10, the step of extracting the modal component with the maximum energy in the fault traveling wave signal except the power frequency comprises:

[0028] S11, extracting each intrinsic modal function component in the fault traveling wave signal by a variational modal decomposition algorithm;

[0029] S12, taking the second largest number in the intrinsic modal function component as the modal component.

[0030] Optionally, in the S10, the step of calculating the sample entropy corresponding to the modal component comprises:

[0031] S13, reconstructing the modal component into a time series of m-dimensional vectors wherein:

[0032] , and is defined as the absolute value of the maximum difference between different vectors:

[0033]

[0034] S14, for , defining the distance r, and counting the number of in the given which is less than or equal to r as , and defining :​​

[0035]

[0036] and define the result of averaging the number of j less than or equal to r in the time series after normalization

[0037]

[0038] S15, by increasing the sequence reconstruction dimension to m +1, the result of averaging the number of j less than or equal to r in the time series after adding one dimension and normalization

[0039]

[0040] S16, calculate the sample entropy corresponding to the modal component according to the following formula

[0041]

[0042] In addition, to achieve the above object, the present application also provides a computer system, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the computer program implements the steps of the tree-shaped multi-branch power grid traveling wave fault locating method according to any one of the above when executed by the processor.

[0043] In addition, to achieve the above object, the present application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program implements the steps of the tree-shaped multi-branch power grid traveling wave fault locating method according to any one of the above when executed by a processor.

[0044] The present application has at least the following beneficial effects:

[0045] 1. The modal sample entropy value near the fault point will increase with the distance of the measuring point, so that the modal sample entropy value of the fault traveling wave presents the characteristics of increasing, and the pair of points with the smallest modal sample entropy value is selected as the upstream key measuring point and the downstream key measuring point of the fault, and the branch number and node number between the initial fault traveling wave position, the upstream key measuring point and the downstream key measuring point are selected as the criterion to further determine the fault section.

[0046] 2. The method is not affected by the transition resistance and the fault distance, has strong noise reduction ability, does not require signal synchronization, has high accuracy of positioning result, and can accurately identify the fault position. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 ​​​​Flowchart of a first embodiment of a tree-shaped multi-branch power distribution network traveling wave fault location method of the present application;

[0048] Figure 2 Systematic diagram of a simulation model involved in an embodiment of the present application;

[0049] Figure 3 Fault traveling wave schematic diagram of each measuring point end involved in an embodiment of the present application;

[0050] Figure 4 T1 end VMD decomposition result involved in an embodiment of the present application;

[0051] Figure 5 Modality component sample entropy value graph of each measuring point involved in an embodiment of the present application;

[0052] Figure 6 T1 end and S7 end initial traveling wave amplitude extraction schematic diagram involved in an embodiment of the present application;

[0053] Figure 7 Architecture schematic diagram of a computer system involved in an embodiment of the present application.

[0054] The implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0055] In order to better understand the above technical solutions, the exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0056] First embodiment

[0057] Referring to Figure 1 , the present embodiment provides a tree-shaped multi-branch power distribution network traveling wave fault location method, which comprises the following steps:

[0058] S10, when the fault traveling wave signal in the power distribution network is acquired, the fault initial traveling wave position corresponding to the fault traveling wave signal is determined, the modal component with the maximum energy other than the power frequency in the fault traveling wave signal is extracted, and the sample entropy corresponding to the modal component is calculated. The nearest point pair with the smallest sample entropy is taken as the fault upstream key measuring point and the fault downstream key measuring point;

[0059] In the embodiment, when a fault occurs in the power distribution network, the pre-installed fault traveling wave detection device in the power distribution network collects the fault traveling wave signal in the power distribution network and determines the position where the fault traveling wave signal is generated, i.e., the initial fault traveling wave position.

[0060] In the embodiment, it can be understood that the fault upstream key measuring point refers to the measuring point close to the side of the fault traveling wave signal, and the fault downstream key measuring point refers to the measuring point farther from the side of the fault traveling wave signal compared with the fault upstream key measuring point.

[0061] Further and optionally, the step of extracting the modal component with the maximum energy except the power frequency in the fault traveling wave signal comprises:

[0062] S11, extracting each intrinsic modal function component in the fault traveling wave signal through a variational mode decomposition algorithm;

[0063] S12, taking the second largest number in the intrinsic modal function component as the modal component.

[0064] In the embodiment, the complex signal can be decomposed into multiple IMFs (intrinsic modal function components) through a variational mode decomposition algorithm (VMD), each IMF is a narrowband component around a center frequency, a plurality of IMF components (such as IMF1-IMF5) are obtained, each IMF represents an oscillation mode of a different frequency band, the low-frequency IMF (such as IMF1) is close to the power frequency (50 Hz) or low-frequency noise, and the high-frequency IMF (such as IMF4-IMF5) reflects the high-frequency transient characteristics of the traveling wave.

[0065] The IMF component (IMF1) with the maximum energy is usually a power frequency component, which belongs to a steady-state signal and is meaningless for fault location. In the VMD decomposition, the IMF2 is usually the modal component with the maximum energy except the power frequency, which contains the main frequency component (usually kHz-MHz level) of the fault traveling wave and avoids the interference of the middle and high frequency noise (IMF3-IMF5).

[0066] Therefore, the second largest number (such as IMF2) in the intrinsic modal function component is selected as the modal component.

[0067] Further and optionally, for the calculation of the sample entropy of the modal component, the following steps can be adopted:

[0068] S13, reconstructing the modal component into a time sequence of m-dimensional vectors , wherein:

[0069] , , and The definition is the absolute value of the maximum difference between different vectors:

[0070]

[0071] S14, for define distance r, statistics given number of j less than or equal to r in number of , define :

[0072]

[0073] And define the number of j less than or equal to r in the time series after normalization and average :

[0074]

[0075] S15, by increasing the sequence reconstruction dimension to m +1, the number of j less than or equal to r in the time series after adding one dimension is obtained :

[0076]

[0077] S16, calculate the sample entropy corresponding to the modal component according to the following formula :

[0078] .

[0079] Finally, the modal sample entropy value near the fault point will increase with the distance of the measuring point position, and the modal sample entropy value of the fault traveling wave will increase, and the value of the modal sample entropy of the nearest point pair m, r, that is, the upstream key measuring point m and the downstream key measuring point r of the fault, is selected.

[0080] S20, the total number of branches and nodes between the upstream key measuring point of the fault and the downstream key measuring point of the fault is taken as a criterion, and the difference between the criterion and each element in the topology information matrix is calculated, wherein the element is composed of the first branch number and the first node number between the fault initial traveling wave position and the upstream key measuring point of the fault.

[0081] In this embodiment, after the upstream key measuring point of the fault and the downstream key measuring point of the fault are determined, the region between the upstream key measuring point of the fault and the downstream key measuring point of the fault is taken, and the total number of branches and nodes in the region is counted.

[0082] It should be noted that the total number of branches and nodes in the distribution network is known data, which can be directly called from the database to obtain the total number of branches and nodes in the region between the upstream key measuring point of the fault and the downstream key measuring point of the fault.

[0083] It can be understood that in the embodiment, the branch refers to a secondary line tapped from a main line (feeder), and the node refers to a cable overhead hybrid node.

[0084] Further and optionally, the expression of the criterion is:

[0085]

[0086] wherein, ;

[0087] wherein, is a decay function, is a refraction coefficient brought by the traveling wave through the branch, is a total number of branches, is a total number of nodes, is an initial voltage traveling wave amplitude of a key measuring point upstream of the fault, is an initial voltage traveling wave amplitude of a key measuring point downstream of the fault, is a refraction coefficient representing the fault traveling wave at the branch.

[0088] wherein, ;

[0089] wherein, is a fault voltage generated by the nth fault point, is an initial voltage traveling wave amplitude of the measuring point S0, and the traveling wave is a reflection coefficient when the traveling wave reaches S0, is a refraction coefficient representing the fault traveling wave at the branch; is a refraction coefficient when the traveling wave reaches SK. wherein, the traveling wave is a reflection coefficient when the traveling wave reaches SK.

[0090] In addition, it needs to be noted that in some optional embodiments, only the branch composed of pure overhead lines is considered, and then:

[0091]

[0092] wherein, is a number of branches.

[0093] In addition, in some optional embodiments, the expression of the decay function can also be:

[0094]

[0095] wherein, is a number of branches through which the initial fault traveling wave reaches the key measuring point Sk downstream of the fault, is the number of hybrid nodes from the fault initial traveling wave to the key measuring point Sk downstream of the fault, and the rest of the parameters are the same as those in the above formula.

[0096] refraction coefficient is the refraction coefficient of the traveling wave at the branch is k times of the refraction coefficient of the traveling wave at the branch, i.e. .

[0097] Each element in the topology information matrix is composed based on the first branch number and the first node number between the fault initial traveling wave position and the key measuring point upstream of the fault. Further and optionally, the expression of the topology information matrix is:

[0098]

[0099] In the formula, is the element in the matrix K, is the first branch number from the fault initial traveling wave to the key measuring point upstream of the fault, is the first node number from the fault initial traveling wave to the key measuring point downstream of the fault, is the refraction coefficient brought by the traveling wave passing through the branch, m is the number of cable sections, and n is the number of nodes.

[0100] Further and optionally, the calculation expression of the difference between the criterion and each element in the topology information matrix includes:

[0101]

[0102] In the formula, is the difference between the criterion and each element in the topology information matrix, is the topology information matrix of order n, is the all-one matrix of the same order, is the attenuation function, is the refraction coefficient brought by the traveling wave passing through the branch, is the total number of branches, is the total number of nodes.

[0103] S30, the section associated with the element corresponding to the minimum difference in each of the differences is determined as the fault section.

[0104] In this embodiment, the minimum difference in each of the differences calculated is the element k i,j corresponding to the minimum difference, and the section k i , k j associated with the element is determined as the fault section finally located.

[0105] In the technical scheme provided in the embodiment, the modal sample entropy value of the fault traveling wave is increased with the distance of the measuring point, the closest point pair with the minimum modal sample entropy value is selected as the key measuring point upstream of the fault and the key measuring point downstream of the fault respectively, and the branch number and the node number between the initial fault traveling wave position, the key measuring point upstream of the fault and the key measuring point downstream of the fault are selected as the criterion to further determine the fault section.

[0106] Second embodiment

[0107] Based on the first embodiment, in the embodiment, considering that there may be invalid elements in the topology information matrix K composed of branches and nodes, for example, the fault occurs in a branch but there is no cable-line mixed node. Therefore, the embodiment also provides a method for verifying the effectiveness of the determined fault section, that is, before the step S30 of determining whether it is a fault section, the following steps are further included:

[0108] S40, determining the size between the minimum difference value and the adaptive threshold value;

[0109] S50, if the minimum difference value is less than or equal to the adaptive threshold value, performing the step S30;

[0110] In S50, if the minimum difference value is less than or equal to the adaptive threshold value, it means that the element in the topology information matrix is a valid element.

[0111] S60, otherwise, the element corresponding to the minimum difference value is removed from the topology information matrix, the difference between the criterion and each element in the updated topology information matrix is recalculated, the current minimum difference value in each difference value is selected, and then the step S40 is returned to be executed until the obtained current minimum difference value is less than or equal to the adaptive threshold value.

[0112] If the condition in S50 is not met, it means that there is a branch but no cable-line mixed node in the section, then the element corresponding to the minimum difference value is removed from the topology information matrix, the difference between the criterion and each element in the updated topology information matrix after the removal is recalculated, the current minimum difference value in each difference value is selected, and then compared with the adaptive threshold value again until the obtained current minimum difference value is less than or equal to the adaptive threshold value, which means that there is no branch but no cable-line mixed node in the section.

[0113] Further and optionally, the calculation expression of the adaptive threshold value includes:

[0114] ;

[0115] In the formula, refractive index caused by the traveling wave passing through the branch, .

[0116] Third embodiment

[0117] Based on any of the above embodiments, the present embodiment provides a simulation model based on the technical solutions involved in the above embodiments, and fault positioning effectiveness verification.

[0118] Referring to Figure 2 The simulation model system shown in the figure is composed of four main feeders: the main feeder 1 contains four type I branches, S1-T1, S4-T2, S5-T4, and S6-T8, respectively, and there is a type II branch T3-T5 on the S5-T4 branch. The main feeder 1 is 29 km long and is composed of overhead lines and cables. The sections S0-S1, S1-S2, S3-S4, S4-S5, S5-S6, and S6-S7 are overhead lines, each 4 km long. The section S2-S3 is a cable line, 5 km long. The feeder head S0 and the feeder tail S7, T5 are equipped with traveling wave measurement devices that can detect and upload traveling wave signals, with a sampling frequency of 1 MHz. The leftmost side is the main power supply, with a voltage level of 10 kV. Each feeder tail uses a 1 MVA constant impedance load.

[0119] The total simulation time is 0.6 s, and a permanent fault occurs at 0.15 s on the overhead line section S4-T2.

[0120] As shown in Figure 3 , the fault traveling wave signal is obtained, and is decomposed by the VMD algorithm, as shown in Figure 4 , the modal component with the maximum energy except the power frequency is extracted and its sample entropy is calculated.

[0121] As shown in Figure 5 , the sample entropy of T1 is much larger than that of the other three measurement points, and T2 is the minimum value, so the selection of key measurement points upstream and downstream of the fault can be realized.

[0122] As can be seen from Figure 6 , the initial traveling wave head amplitude of the line mode voltage at T1 is 6.64 kV, and the initial traveling wave head amplitude of the line mode voltage at S7 is 17.51 kV, so we can get:

[0123]

[0124] Since the fault occurs in the section S4-T2 and the section S4-S5 relative to the traveling wave detection device, the and values obtained are the same, so the is also calculated combined with the traveling wave obtained at S7. Convenient for screening branch and main fault. Then the topology information matrix is established for the existing topology.

[0125]

[0126]

[0127] Next, the characteristic element of the fault discrimination coefficient matrix is calculated as .

[0128]

[0129] From the above matrix, by knowing the topological structure, the effective elements in the dashed box can be obtained, and other invalid elements are excluded, according to , and , , by adaptive threshold discrimination coefficient, combined with the fault discrimination coefficient matrix , it is judged that and are respectively 1 and 2, corresponding to the fault topology, it can be concluded that the fault may occur on the section S4-T2 and the section S4-S5, for this, the fault discrimination coefficient matrix about the traveling wave detection device at S7 is constructed Repeat the above steps about the traveling wave detection device, finally and are respectively 0 and 3, since the fault is assumed to occur in the section S4-S5, and should be respectively 0 and 2, so the fault position is in the section S4-T2:

[0130]

[0131] Combined with the topology, the final positioning result is consistent.

[0132] As an implementation scheme, Figure 7 is the architecture diagram of the hardware running environment of the computer system involved in the embodiment scheme of the application.

[0133] As Figure 7As shown, the computer system can include: a processor 1001, such as a CPU, a memory 1005, a user interface 1003, a network interface 1004, and a communication bus 1002. The communication bus 1002 is used to realize the connection communication between the components. The user interface 1003 can include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 can also include a standard wired interface, a wireless interface. The network interface 1004 can optionally include a standard wired interface, a wireless interface (such as a WI-FI interface). The memory 1005 can be a high-speed RAM memory, or a stable memory (non-volatile memory) such as a magnetic disk memory. The memory 1005 can also be a storage device independent of the aforementioned processor 1001.

[0134] Those skilled in the art can understand that, Figure 7 The computer system architecture shown in the figure does not constitute a limitation on the computer system, and can include more or fewer components than the figure, or combine certain components, or different component arrangements.

[0135] As Figure 7 As shown, the memory 1005 as a storage medium can include an operating system, a network communication module, a user interface module, and a computer program. The operating system is a program that manages and controls the hardware and software resources of the computer system, and the running of the computer program and other software or programs.

[0136] In Figure 7 In the computer system shown, the user interface 1003 is mainly used to connect the terminal and communicate data with the terminal; the network interface 1004 is mainly used for the background server and communicates data with the background server; and the processor 1001 can be used to call the computer program stored in the memory 1005.

[0137] In this embodiment, the computer system includes: a memory 1005, a processor 1001, and a computer program stored on the memory and executable on the processor, wherein:

[0138] When the processor 1001 calls the computer program stored in the memory 1005, the following operations are performed:

[0139] S10, when the fault traveling wave signal in the power distribution network is acquired, the fault initial traveling wave position corresponding to the fault traveling wave signal is determined, the modal component with the maximum energy except the power frequency in the fault traveling wave signal is extracted, and the sample entropy corresponding to the modal component is calculated. The nearest point pair with the smallest sample entropy is used as the fault upstream key measuring point and the fault downstream key measuring point;

[0140] S20, calculate the difference between the criterion and each element in the topology information matrix, wherein the element is composed of the first branch number and the first node number between the fault initial traveling wave position and the upstream key measurement point of the fault;

[0141] S30, determine the section associated with the element corresponding to the minimum difference in each difference as the fault section.

[0142] When the processor 1001 invokes the computer program stored in the memory 1005, the following operations are performed:

[0143] S40, determine the size between the minimum difference and the adaptive threshold value;

[0144] S50, if the minimum difference is less than or equal to the adaptive threshold value, execute the step S30;

[0145] S60, otherwise, remove the element corresponding to the minimum difference from the topology information matrix, recalculate the difference between the criterion and each element in the updated topology information matrix, select the current minimum difference in each difference, and return to execute step S40 until the obtained current minimum difference is less than or equal to the adaptive threshold value.

[0146] When the processor 1001 invokes the computer program stored in the memory 1005, the following operations are performed:

[0147] S11, extract each intrinsic modal function component in the fault traveling wave signal by variational modal decomposition algorithm;

[0148] S12, take the second largest number in the intrinsic modal function component as the modal component.

[0149] When the processor 1001 invokes the computer program stored in the memory 1005, the following operations are performed:

[0150] S13, reconstruct the modal component into a time series of m-dimensional vectors ,

[0151] , , and The distance r is defined as the absolute value of the maximum difference between different vectors:

[0152]

[0153] S14, for Define the distance r, and count the less than or equal to r in the given The number is ,definition :

[0154]

[0155] Furthermore, the average of the number of j values ​​less than or equal to r in the time series is defined after normalization. :

[0156]

[0157] S15, by increasing the sequence reconstruction dimension to m + 1, the number of j values ​​less than or equal to r after adding one dimension to the time series is normalized and then averaged. :

[0158]

[0159] S16, Calculate the sample entropy corresponding to the modal component according to the following formula. :

[0160] .

[0161] Furthermore, those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in a computer system to implement the process steps of the embodiments of the above methods.

[0162] Therefore, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the various steps of the tree-structured multi-dominated power grid traveling wave fault location method as described in the above embodiments.

[0163] The computer-readable storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0164] It should be noted that, since the storage medium provided in the embodiments of this application is the storage medium used to implement the methods of the embodiments of this application, those skilled in the art can understand the specific structure and variations of the storage medium based on the methods described in the embodiments of this application, and therefore will not be repeated here. All storage media used in the methods of the embodiments of this application fall within the scope of protection of this application.

[0165] Those skilled in the art will appreciate that embodiments of the application can be readily used as a method, apparatus such as a system, or computer program product. Accordingly, the application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the application can take the form of a computer program product on one or more computer readable storage media (including, but not limited to, disk memory, CD-ROMs, optical storage devices, etc.) embodying computer readable program code.

[0166] The application is described herein with reference to the Figures, which illustrate the embodiments of the application. The drawings described are only schematic and are non-limiting. In the drawings, like or similar elements are designated with the same reference numerals. Each example in this document is provided by way of explanation of the application. There is no intention to limit the application to these examples, which are provided to more fully describe the application. In the drawings: Figure 1 Figure 1

[0167] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart or flowsheet block or blocks. Figure 1 Figure 1

[0168] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart or flowsheet block or blocks. Figure 1 Figure 1 Figure 1

[0169] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the application, the application can be practiced otherwise than as specifically described.​​​​​​

Claims

1. A method for locating traveling wave faults in a tree-structured multi-dominated power grid, characterized in that, The method comprises the following steps: S10, when a fault traveling wave signal in a power distribution network is acquired, determining a fault initial traveling wave position corresponding to the fault traveling wave signal, extracting a modal component with maximum energy except for a power frequency in the fault traveling wave signal, and calculating a sample entropy corresponding to the modal component, taking a pair of adjacent points with minimum sample entropy as a fault upstream key measuring point and a fault downstream key measuring point; S20, taking a total number of branches and a total number of nodes between the fault upstream key measuring point and the fault downstream key measuring point as a criterion, calculating a difference value between the criterion and each element in a topology information matrix, wherein the element is composed of a first branch number and a first node number between the fault initial traveling wave position and the fault upstream key measuring point; S30, determining a section associated with an element corresponding to a minimum difference value in each difference value as a fault section; In the S20, an expression of the criterion is: ； wherein ; wherein, is a decay function, is a refractive index brought by the traveling wave passing through the branch, is the total number of branches, is the total number of nodes, is the initial voltage traveling wave amplitude of the upstream key measuring point of the fault, is the initial voltage traveling wave amplitude of the downstream key measuring point of the fault, is a refractive index representing the fault traveling wave at the branch; In the S20, an expression of the topology information matrix is: ； wherein is an element in matrix K, is the first branch number of the fault initial traveling wave to the fault upstream key measuring point, is the first node number of the fault initial traveling wave to the fault downstream key measuring point, is the refraction coefficient brought by the traveling wave through the branch, m is the cable segment number, and n is the node number.

2. The method of claim 1, wherein the tree-structured multi-branch power distribution network is a tree-structured multi-branch power distribution network having a plurality of branches, and the method further comprises: determining a fault location of the tree-structured multi-branch power distribution network based on the plurality of fault location information. In the S20, the calculation expression of the difference value between the criterion and each element in the topology information matrix comprises: ； wherein, is the difference between the criterion and each element in the topological information matrix, is m × n is the topological information matrix of order is m × n is the all-one matrix of the same order, is the attenuation function, is the refraction coefficient due to the passage of the travelling wave through the branch, is the total number of branches, is the total number of nodes.

3. The tree-structured multi-dominated power grid traveling wave fault location method as described in claim 1, characterized in that, Before the step S30, the method further comprises: S40, determining a size between the minimum difference value and an adaptive threshold value; S50, if the minimum difference value is less than or equal to the adaptive threshold value, executing the step S30; S60, otherwise, eliminating the element corresponding to the minimum difference value from the topology information matrix, recalculating the difference value between the criterion and each element in the updated topology information matrix, selecting a current minimum difference value in each difference value, and returning to execute the step S40 until the obtained current minimum difference value is less than or equal to the adaptive threshold value.

4. The tree multi-branched power network traveling wave fault location method of claim 3, wherein, The adaptive threshold The computational expression of the adaptive threshold comprises: ; wherein is the refractive index of the waveguide material, .

5. The method of claim 1, wherein the tree-structured multi-branch power network is a radial network. In the S10, the step of extracting the modal component with maximum energy except for the power frequency in the fault traveling wave signal comprises: S11, extracting each intrinsic modal function component in the fault traveling wave signal by a variational modal decomposition algorithm; S12, taking a second largest number in the intrinsic modal function component as the modal component.

6. The tree multi-branched power network traveling wave fault location method of claim 1 or 5, wherein, In the S10, the step of calculating the sample entropy corresponding to the modal component comprises: S13, reconstructing the modal components into a time series of m-dimensional vectors wherein: , , and defined as the absolute value of the maximum difference between different vectors: ； S14, for define distance r, count the number of points in the set less than or equal to r number of points define : ； and defining the result of normalizing and averaging the number of j's in the time series that are less than or equal to r : ； S15, by increasing the sequence reconstruction dimension to m + 1, get the number of j which is less than or equal to r after the time series is added with one dimension, normalized and averaged : ； S16, calculate sample entropy corresponding to the modal component according to the following formula : 。 7. A computer system, characterized by The computer system comprises a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is executed by the processor to implement the steps of the tree-shaped multi-branch power distribution network traveling wave fault positioning method in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the tree-shaped multi-branch power distribution network traveling wave fault positioning method in any one of claims 1 to 6.

Images