CN111381128A

CN111381128A - Power distribution network fault positioning method and device and server

Info

Publication number: CN111381128A
Application number: CN201911352673.2A
Authority: CN
Inventors: 邓丰; 徐帆; 蒲涛; 梅龙军; 祖亚瑞
Original assignee: Changsha University of Science and Technology
Current assignee: Changsha University of Science and Technology
Priority date: 2019-12-25
Filing date: 2019-12-25
Publication date: 2020-07-07
Anticipated expiration: 2039-12-25
Also published as: CN111381128B

Abstract

The application belongs to the technical field of power distribution network fault positioning, and provides a power distribution network fault positioning method, device and server, which are used for solving the technical problems that positioning accuracy is low and a power distribution network with a complex topological structure is difficult to deal with due to the influence of factors such as initial traveling wave head extraction errors. The method comprises the steps of firstly determining the head end of a main feeder line, the tail end of each branch line and each branch node, constructing a fault time characteristic matrix after an actual fault occurs, respectively performing primary fitting on a reference time characteristic matrix and the fault time characteristic matrix by adopting a least square method, determining the branch nodes corresponding to elements meeting the primary fitting relation as non-fault branch nodes, and determining the regions corresponding to the branch nodes except the non-fault branch nodes as fault candidate regions. And further carrying out accurate fault point positioning on the fault candidate area. The method and the device can be suitable for large-scale power distribution networks with complex topological structures, and are low in algorithm complexity, easy to implement and high in practicability.

Description

Power distribution network fault positioning method and device and server

Technical Field

The present application relates to the field of distribution network fault location technologies, and in particular, to a method, an apparatus, and a server for locating a fault in a distribution network.

Background

In China, most power distribution networks adopt a neutral point non-effective grounding mode, most faults in a power distribution system are single-phase grounding faults, the current amplitude of the single-phase grounding faults is small, and the traditional power distribution network line selection and fault location method is very difficult.

In recent years, various line selection methods have been proposed, including an injection signal method, an information fusion method, and a fault signal method. The signal injection method is easy to interfere and not easy to apply to the field, and the method needs to be specially provided with a signal power supply device and is complex to deploy. The information fusion method is suitable for practical use because the method can extract effective fault information sufficiently and process the fault information effectively. The fault signal method is divided into a steady-state component method and a transient-state component method, when a line has a fault, the steady-state component is weak, and the transient-state component signal energy is large, so that the fault signal method can be used for fault line selection.

The topological structure of the power distribution network is complex, and a great number of branches exist on the feeder line, so that the positioning of the fault point becomes a difficult problem. The traditional power distribution network fault location method based on the steady-state component comprises an impedance method, an injection signal method, a fault location method based on power frequency and the like. The impedance method is greatly influenced by the accuracy of the line parameters of the power distribution network and the transition resistance, and has the problem of false fault points; the reliability of the signal injection method is influenced by intermittent electric arcs and transition resistance, and the practical application is limited; the power frequency ranging method can only realize zone positioning, has false fault points and has low ranging accuracy.

At present, a traveling wave positioning method is a feasible scheme for realizing accurate positioning of the faults of the power distribution network. The power distribution network line selection and fault positioning technology based on the traveling wave is basically not influenced by factors such as fault types, system parameters, line asymmetry and the like, and the line selection and positioning accuracy is high. However, the power distribution network mostly presents a tree-shaped radial structure and has short lines, the existing partial traveling wave positioning scheme depends on the extraction accuracy of the initial traveling wave head, the initial traveling wave extraction is influenced by factors such as a network topology structure, lightning stroke or high-frequency noise, and the wave head extraction has errors of different degrees, so that the traveling wave fault positioning accuracy is not high.

In addition, due to the power distribution network with a complex topological structure, fault data often has the characteristics of large data volume, multiple points and wide area, in the existing traveling wave fault scheme, a method for realizing line selection and fault positioning by fusing whole network data has huge data processing amount and delay in network transmission, so that the method is often difficult to deal with the large-scale power distribution network with the complex topological structure, and the engineering application is limited.

Disclosure of Invention

Problem (A)

In summary, how to provide a fault location method that does not depend on the accuracy of extracting the initial traveling wave head of the fault and can cope with the complex topology distribution network becomes a problem to be solved by those skilled in the art.

(II) technical scheme

In a first aspect of the embodiments of the present application, a power distribution network fault location method is provided, including:

determining the head end of a main feeder line, the tail end of the main feeder line, the tail end of each branch line and each branch node of a distribution network in a positioning range;

after an actual fault occurs, constructing a first fault time characteristic matrix and a second fault time characteristic matrix; the elements in the first fault time characteristic matrix are respectively used for representing the actual fault traveling wave arrival time differences corresponding to a first end and a main feeder line head end, each branch line tail end and a main feeder line tail end, and the first end is any one of the main feeder line head end, the main feeder line tail end and each branch line tail end; elements in the second fault time characteristic matrix are respectively used for representing actual fault traveling wave arrival time differences corresponding to a second tail end and the head end of the main feeder line, the tail ends of all branch lines and the tail end of the main feeder line, wherein the second tail end is one of the head end of the main feeder line, the tail end of the main feeder line and the tail end of all branch lines except the first tail end;

reading a first reference time characteristic matrix and a second reference time characteristic matrix which are prestored; the elements in the first reference time characteristic matrix are respectively used for representing the arrival time difference of the simulated fault traveling wave corresponding to the first tail end and the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line; elements in the second reference time characteristic matrix are respectively used for representing the arrival time difference of the simulated fault traveling wave corresponding to the second tail end and the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line;

performing primary fitting on the first reference time characteristic matrix and the first fault time characteristic matrix, and the second reference time characteristic matrix and the second fault time characteristic matrix respectively by adopting a least square method;

determining branch nodes corresponding to elements satisfying a first-time fitting relationship in the first reference time characteristic matrix and the first failure time characteristic matrix and branch nodes corresponding to elements satisfying a first-time fitting relationship in the second reference time characteristic matrix and the second failure time characteristic matrix as non-failure branch nodes, and determining regions corresponding to branch nodes except the non-failure branch nodes in each branch node as failure candidate regions.

Optionally, after the actual fault occurs, before constructing the first fault time characteristic matrix and the second fault time characteristic matrix, the method further includes:

taking the head end of the main feeder line as a first tail end and the tail end of the main feeder line as a second tail end;

setting a simulated fault at the head end of the main feeder line, and acquiring the arrival time of a simulated fault traveling wave corresponding to the head end of the main feeder line, the tail end of the main feeder line and the tail ends of the branch lines;

respectively calculating the arrival time of the simulated fault traveling wave recorded at the tail end of the main feeder line and the arrival time of the simulated fault traveling wave recorded at the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line, and sequencing the obtained time differences according to a preset sequence to form a first reference time characteristic matrix;

setting a simulated fault at the tail end of a main feeder line, and acquiring the arrival time of a simulated fault traveling wave corresponding to the head end of the main feeder line, the tail end of the main feeder line and the tail end of each branch line;

respectively calculating the arrival time of the simulated fault traveling wave recorded by the head end of the main feeder line and the arrival time of the simulated fault traveling wave recorded by the head end of the main feeder line, the tail ends of the branch lines and the tail end of the main feeder line, and sequencing the obtained time differences according to the preset sequence to form a second reference time characteristic matrix;

after an actual fault occurs, constructing a first fault time characteristic matrix and a second fault time characteristic matrix, specifically comprising:

after an actual fault occurs, acquiring actual fault traveling wave arrival time corresponding to the head end of a main feeder line, the tail end of the main feeder line and the tail end of each branch line;

respectively calculating the time difference between the actual fault traveling wave arrival time recorded at the tail end of the main feeder line and the actual fault traveling wave arrival time recorded at the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line, and sequencing the obtained multiple time differences according to the preset sequence to form a first fault time characteristic matrix;

and respectively calculating the time difference between the actual fault traveling wave arrival time recorded at the head end of the main feed line and the actual fault traveling wave arrival time recorded at the head end of the main feed line, the tail end of each branch line and the tail end of the main feed line, and sequencing the obtained time differences according to the preset sequence to form a second fault time characteristic matrix.

Optionally, after determining each branch node, before determining, in each branch node, an area corresponding to a branch node other than the non-faulty branch node as a faulty candidate area, the method further includes:

generating a branch node set, wherein the branch node set comprises all branch nodes;

determining, as a candidate fault region, a region corresponding to a branch node other than the non-faulty branch node in each branch node, specifically including:

adding the non-fault branch nodes determined by fitting the first reference time characteristic matrix and the first fault time characteristic matrix into a first non-fault branch node set, and adding the non-fault branch nodes determined by fitting the second reference time characteristic matrix and the second fault time characteristic matrix into a second non-fault branch node set;

merging the first set of non-failed branch nodes and the second set of non-failed branch nodes into a set of non-failed branch nodes;

and solving a complement of the non-fault branch node set from the branch node set, and taking the area corresponding to the branch node in the complement as a fault candidate area.

Optionally, after determining, as a candidate failure region, a region corresponding to a branch node other than the non-failure branch node in each branch node, the method further includes:

if the complementary set is an empty set, judging that the main feeder line has a fault;

calculating the distance between each branch node in the first non-fault branch node set and each branch node in the second non-fault branch node set, and determining a main feeder line between two closest branch nodes as a fault section;

if the supplement set has only one branch node, judging that a single branch line fault occurs, and determining a branch line corresponding to the branch node as a fault branch;

if a plurality of branch nodes exist in the complementary set, judging that a multi-branch line fault occurs, marking the branch nodes positioned on the main feeder line in the complementary set as main branch nodes, acquiring a topology structure diagram of the distribution network in the positioning range, deleting the branch lines corresponding to the non-fault branch nodes, the main feeder line tail ends and the main feeder line intervals between the main feeder line tail ends and the main branch nodes in the topology structure diagram, and reserving the main feeder line intervals between the main feeder line head ends and the main branch nodes and the multi-branch lines corresponding to the plurality of branch nodes to form the next to-be-positioned topology network.

Optionally, after the next failure candidate region is formed, the method further includes:

constructing a third reference time characteristic matrix and a fourth reference time characteristic matrix, and a third fault time characteristic matrix and a fourth fault time characteristic matrix corresponding to the next fault candidate region;

performing primary fitting on the third reference time characteristic matrix and the third fault time characteristic matrix, and the fourth reference time characteristic matrix and the fourth fault time characteristic matrix respectively by using a least square method;

determining branch nodes corresponding to elements satisfying a primary fitting relationship in the third reference time characteristic matrix and the third failure time characteristic matrix and branch nodes corresponding to elements satisfying a primary fitting relationship in the fourth reference time characteristic matrix and the fourth failure time characteristic matrix as non-failure branch nodes, and determining regions corresponding to branch nodes except the non-failure branch nodes in each branch node included in the next failure candidate region as the next failure candidate region;

and if the next fault candidate area contains a plurality of branch nodes, circularly executing the steps from the head end of the main feeder line, the tail end of each branch line and each branch node of the distribution network in the determined positioning range to the step of determining the fault candidate area until only one branch line is contained in the fault candidate area.

and when the fault candidate region is determined to only contain one branch line, selecting two tail ends from the tail ends of the branch lines, pairwise matching the two tail ends with the tail end of the branch line, and calculating the position of the fault point based on a double-end traveling wave positioning method.

In a second aspect of the embodiments of the present application, there is provided a power distribution network fault location device, including:

the determining unit is used for determining the head end of a main feeder line, the tail end of the main feeder line, the tail end of each branch line and each branch node of the distribution network in the positioning range;

the construction unit is used for constructing a first fault time characteristic matrix and a second fault time characteristic matrix after an actual fault occurs; the elements in the first fault time characteristic matrix are respectively used for representing the actual fault traveling wave arrival time differences corresponding to a first end and a main feeder line head end, each branch line tail end and a main feeder line tail end, and the first end is any one of the main feeder line head end, the main feeder line tail end and each branch line tail end; elements in the second fault time characteristic matrix are respectively used for representing actual fault traveling wave arrival time differences corresponding to a second tail end and the head end of the main feeder line, the tail ends of all branch lines and the tail end of the main feeder line, wherein the second tail end is any one of the head end of the main feeder line, the tail end of the main feeder line and the tail end of all branch lines except the first tail end;

the fitting unit is used for reading a first reference time characteristic matrix and a second reference time characteristic matrix which are prestored; the elements in the first reference time characteristic matrix are respectively used for representing the arrival time difference of the simulated fault traveling wave corresponding to the first tail end and the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line; elements in the second reference time characteristic matrix are respectively used for representing the arrival time difference of the simulated fault traveling wave corresponding to the second tail end and the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line; performing primary fitting on the first reference time characteristic matrix and the first fault time characteristic matrix, and the second reference time characteristic matrix and the second fault time characteristic matrix respectively by adopting a least square method;

and a fault elimination unit, configured to determine, as non-faulty branch nodes, branch nodes corresponding to elements that satisfy a first-order fitting relationship in the first reference time feature matrix and the first fault time feature matrix, and branch nodes corresponding to elements that satisfy a first-order fitting relationship in the second reference time feature matrix and the second fault time feature matrix, and determine, as fault candidate regions, regions corresponding to branch nodes other than the non-faulty branch nodes in each branch node.

Optionally, after the actual fault occurs and before the first fault time characteristic matrix and the second fault time characteristic matrix are constructed, the constructing unit is further configured to:

after an actual fault occurs, a first fault time characteristic matrix and a second fault time characteristic matrix are constructed, and the construction unit is specifically configured to:

Optionally, after determining each branch node, before determining, in each branch node, an area corresponding to a branch node other than the non-faulty branch node as a faulty candidate area, the determining unit is further configured to:

generating a set of branch nodes, the set of branch nodes including the respective branch nodes;

when the area corresponding to the branch node except the non-faulty branch node among the branch nodes is determined as a faulty candidate area, the determining unit is specifically configured to:

adding the non-fault branch nodes determined by fitting the first reference time characteristic matrix and the first fault time characteristic matrix into a first non-fault branch node set, and adding the non-fault branch nodes determined by fitting the second reference time characteristic matrix and the second fault time characteristic matrix into a second non-fault branch node set; merging the first set of non-failed branch nodes and the second set of non-failed branch nodes into a set of non-failed branch nodes;

solving a complement of the non-fault branch node set from the branch node set, and taking a region corresponding to a branch node in the complement as a fault candidate region;

after determining, as a candidate failure region, a region corresponding to a branch node other than the non-failed branch node among the branch nodes, the failure removal unit is further configured to:

if the complementary set is an empty set, judging that the main feeder line has a fault; calculating the distance between each branch node in the first non-fault branch node set and each branch node in the second non-fault branch node set, and determining a main feeder line between two closest branch nodes as a fault section;

if a plurality of branch nodes exist in the complementary set, judging that a multi-branch line fault occurs, marking the branch nodes positioned on the main feeder line in the complementary set as main branch nodes, acquiring a topology structure diagram of the distribution network in the positioning range, deleting the non-fault branch nodes, the branch lines corresponding to the non-fault branch nodes, the main feeder line tail ends and the main feeder line intervals between the main feeder line tail ends and the main branch nodes in the topology structure diagram, and reserving the main feeder line intervals between the main feeder line head ends and the main branch nodes and the multi-branch lines corresponding to the branch nodes to form a next to-be-positioned topology network.

In a third aspect of the embodiments of the present application, there is further provided a server, including: a memory, a processor, wherein,

the memory to store executable instructions;

the processor is used for reading and executing the executable instructions stored in the memory so as to realize the method of any one of the above.

(III) advantageous effects

In the embodiment of the application, the reference time characteristic matrix and the fault time characteristic matrix are constructed, the least square method is adopted to carry out one-time fitting on the reference time characteristic matrix and the fault time characteristic matrix, the error influence is eliminated, the non-fault branch node can be determined according to the fitting result, the fault candidate area is further obtained, and the specific fault occurrence point can be further accurately positioned based on the determined fault candidate area. The method takes the arrival time difference of the initial traveling wave heads at different tail ends as the most basic element of quantitative calculation, eliminates the influence of the extraction error of the initial traveling wave heads, and has higher positioning accuracy; in addition, for the power distribution network with a complex topological structure, the method only needs to establish a corresponding reference time characteristic matrix and a corresponding fault time characteristic matrix, the data processing capacity of the least square method is not high, a processor with general processing capacity can deal with the data processing capacity, and various problems caused by huge data processing capacity are avoided;

further, when the determined fault candidate region is a complex local network comprising a plurality of branches, the steps of constructing the time characteristic matrix and performing primary fitting by a least square method and determining the fault candidate region can be executed circularly, non-fault branch nodes are further removed, and the range of the fault candidate region is gradually reduced until a single fault branch is determined;

furthermore, after the single fault branch with the fault is determined, the specific fault point position on the single fault branch can be further calculated through a double-end traveling wave positioning method, and the absolute error of fault positioning is within a range of 50 meters through a simulation experiment.

Drawings

FIG. 1 is a flow chart of a method for locating faults in a power distribution network according to the present application;

fig. 2 is a schematic network diagram of a local topology structure of a power distribution network corresponding to a domain in an embodiment of the present application;

FIG. 3 is a schematic flow chart diagram illustrating one embodiment of a fault location method in an embodiment of the present application;

FIG. 4 is a schematic structural diagram of a main feeder line in an embodiment of the present application in which a fault occurs;

FIG. 5 is a schematic structural diagram of a single branch fault in an embodiment of the present application;

FIG. 6 is a schematic diagram of a network structure with a new topology determined anew in an embodiment of the present application;

FIGS. 7-10 are diagrams illustrating the results of a first fit using least squares;

fig. 11 is a schematic structural diagram of a power distribution network fault location device according to an embodiment of the present application;

fig. 12 is a schematic structural diagram of a server according to an embodiment of the present application.

Detailed Description

Embodiments of the present application will be described in further detail below with reference to the drawings and examples. The following examples are intended to illustrate the present application but are not intended to limit the scope of the present application.

In the description of the present application, unless otherwise specified, "a plurality" means two or more; the terms "upper", "lower", "left", "right", "inner", "outer", "front", "rear", "head", "tail", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present application and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present application. Furthermore, the terms "first," "second," "third," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

In the description of the present application, it is to be noted that, unless otherwise explicitly specified or limited, the terms "connected" and "connected" are to be interpreted broadly, e.g., as being fixed or detachable or integrally connected; can be mechanically or electrically connected; may be directly connected or indirectly connected through an intermediate. The specific meaning of the above terms in the present application can be understood in a specific case by those of ordinary skill in the art.

The power distribution network fault positioning method provided by the embodiment of the application is applicable to power distribution networks with various topological structures. For a power distribution network with a complex topological structure in a positioning range, firstly, the power distribution network is determined to comprise a plurality of main feeders, the power distribution network is divided into a plurality of domains with the number equal to that of the main feeders, and one domain comprises one main feeder and branch lines connected with the main feeder. For a sub-domain formed by a main feeder line and branch lines connected with the main feeder line, accurate positioning can be performed according to the fault positioning method provided by the embodiment of the application, that is, the minimum application range of the positioning method provided by the embodiment of the application is a local topology network formed by a main feeder line and branch lines connected with the main feeder line. In the local topology network, the head end and the tail end of the main feeder line and the tail end of each branch line are provided with traveling wave collecting devices.

Referring to fig. 1, the method for locating a fault of a power distribution network provided by the embodiment of the application includes the following steps:

s101: and determining the head end of a main feeder line, the tail end of the main feeder line, the tail end of each branch line and each branch node of the distribution network within the positioning range.

In the embodiment of the application, the distribution network in the positioning range is a local topology network comprising one main feeder line and only one main feeder line. The main feeder is generally consistent with an actual main feeder in a distribution network, and for the distribution network without the definite main feeder, a line can be selected as the main feeder according to positioning needs, and the main feeder is not unique and can be relatively determined according to actual positioning needs.

First, the main feeder head end, the main feeder tail end, each branch line tail end, and each branch node need to be specified. For example, referring to fig. 2, the local topology network shown in fig. 2 is a sub-domain, the sub-domain includes a main feeder (i.e., the feeder 1 shown in fig. 2), a head end of the main feeder 1 is labeled as 1#, a tail end of the main feeder is labeled as 8#, tail ends of branch lines are respectively labeled as 2# -7#, the sub-domain includes 6 branch nodes a, b, c, d, e, and g, and branch lines connected to the main feeder 1 are respectively a-2, b-3, e-4, c-d-e-5, d-6, and g-7. And the head end and the tail end of the main feeder line and the tail end of each branch line are provided with traveling wave collecting devices. According to the local distribution network shown in fig. 1, it can be determined that the head end of the main feeder is 1#, the tail end of the main feeder is 8#, the tail ends of the branch lines are respectively 2# -7#, and the branch nodes are respectively a, b, c, d, e and g.

After determining the topology of the head end, the tail end, etc. of the main feeder line, before S102, a reference time characteristic matrix after the occurrence of the simulated fault should be constructed.

Specifically, the reference time feature matrix may be constructed in the following two ways:

the first method is as follows: main feeder (actual main feeder) head-to-tail mode.

In the actual distribution network topology structure, whether each line is a main feeder line or a branch line is clear, and in the embodiment of the application, there is one actual main feeder line in each sub-domain. The first way is to use the actual main feeder head end as the first end and the main feeder end as the second end.

Firstly, constructing a reference time characteristic matrix corresponding to the head end of a main feeder line:

setting a simulated fault at the head end of the main feeder line, acquiring simulated fault traveling wave arrival time corresponding to the head end of the main feeder line, the tail end of the main feeder line and the tail ends of the branch lines, respectively calculating the simulated fault traveling wave arrival time recorded at the tail end of the main feeder line and the simulated fault traveling wave arrival time recorded at the head end of the main feeder line, the tail ends of the branch lines and the tail end of the main feeder line, and sequencing the obtained time differences according to a preset sequence to form a first reference time characteristic matrix.

In the embodiments of the present application, the arrival time of the fault traveling wave refers to the arrival time of the initial traveling wave head of the simulated fault or the actual fault collected by the traveling wave fault collection device, unless otherwise specified.

For example, assuming that a simulated fault occurs at the head end of the main feeder line k, the tail ends of the plurality of branch lines, and the tail end of the main feeder line k are respectively marked as 1# -n #, and the arrival time of the initial traveling wave head of the simulated fault traveling wave collected by the traveling wave collecting devices at the head end, the tail end, and the tail end of the main feeder line k is t_iWherein the arrival time of the initial traveling wave head calibrated at the head end of the main feed line is t₁The arrival time of the initial traveling wave head calibrated at the tail end is t_nRespectively calculating the time difference between the arrival time of the initial traveling wave head of the simulated fault traveling wave collected at the tail end of the main feeder line and the arrival time of the initial traveling wave head collected at the head end, the tail end and the tail end of each branch line of the main feeder line to obtain a head end reference time characteristic matrix (namely a first reference time characteristic matrix) of the main feeder line k

Next, constructing a reference time characteristic matrix corresponding to the tail end of the main feeder line:

setting a simulated fault at the tail end of the main feeder line, acquiring simulated fault traveling wave arrival time corresponding to the head end of the main feeder line, the tail end of the main feeder line and the tail end of each branch line, respectively calculating the simulated fault traveling wave arrival time recorded by the head end of the main feeder line and the time difference between the simulated fault traveling wave arrival time recorded by the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line, and sequencing the obtained time differences according to the preset sequence to form a second reference time characteristic matrix.

For example, assuming that a simulated fault occurs at the end of the main feeder line k, the arrival time of the simulated fault traveling wave head collected at the head end of the main feeder line k is time-differentiated from the arrival time of the initial traveling wave head collected at the head end of the main feeder line, the end of the main feeder line and the end of each branch line, so as to obtain a reference time characteristic matrix (i.e., a second reference time characteristic matrix) at the end of the main feeder line k

The second method comprises the following steps: and selecting two terminals to construct a reference time characteristic matrix.

In the second embodiment, two terminals are selected from the n branch line terminals as the first terminal and the second terminal, respectively, for example, the ith branch line terminal is selected as the first terminal, the mth branch line terminal is selected as the second terminal, and i < m < n are positive integers.

In the second mode, the actual main feeder line is not selected as the main feeder line which is referred to when the time characteristic matrix is constructed, but a line which is composed of branch lines is selected as the virtual main feeder line, and the corresponding reference time characteristic matrix is constructed on the basis that the head end and the tail end of the virtual main feeder line are respectively provided with the simulation faults.

It should be noted that the first end and the second end should avoid selecting two adjacent ends as much as possible, and selecting two adjacent ends or two ends with a short distance increases the complexity of the positioning algorithm. When fault location is performed, the head end of an actual main feeder line in a sub-domain may be used as a first end, and the end of the actual main feeder line is used as a second end, to perform fault location, or to re-determine the main feeder line, that is, when a branch line end is selected as the first end or the second end, a branch line connecting the first end and the second end is defined as a virtual main feeder line, and a process of selecting the first end and the second end, that is, a process of re-determining a virtual main feeder line, may be used.

Preferably, when the first terminal and the second terminal are selected, the branch line structures on two sides of the virtual main feeder line are distributed symmetrically as much as possible, so that the situation that the branch line topology structure on one side is too complex to cause the fault location algorithm to need to be executed repeatedly and circularly is avoided, the complexity of the fault location algorithm is reduced, and faster fault point location is realized.

Correspondingly, assuming that the ith branch line tail end has a simulated fault, the head end and the tail end of the main feeder line k and the tail ends of the multiple branch lines are respectively marked as 1# -n #, and the arrival time of the initial traveling wave head of the simulated fault traveling wave collected by the traveling wave collecting devices at the head end, the tail end and the tail end of the main feeder line k is t # -n #, wherein the traveling wave head of the simulated fault traveling wave collected by the traveling wave collecting_iWherein the arrival time of the initial traveling wave head calibrated at the head end of the main feed line is t₁The arrival time of the initial traveling wave head calibrated at the tail end is t_nRespectively calculating the time difference between the arrival time of the initial traveling wave head of the simulated fault traveling wave collected at the tail end of the mth branch line and the arrival time of the initial traveling wave head collected at the head end, the tail end and the tail end of each branch line to obtain a first reference time characteristic matrix of

Correspondingly, assuming that the mth branch line tail end has a simulated fault, the head end and the tail end of the main feeder line k and the tail ends of the multiple branch lines are respectively marked as 1# -n #, and the arrival time of the initial traveling wave heads of the simulated fault traveling waves collected by the traveling wave collecting devices at the head end, the tail end and the tail end of the main feeder line k is t # -_iWhen the initial traveling wave head calibrated at the head end of the main feeder line arrivesIs carved as t₁The arrival time of the initial traveling wave head calibrated at the tail end is t_nRespectively calculating the time difference between the arrival time of the initial traveling wave head of the simulated fault traveling wave collected at the tail end of the ith branch line and the arrival time of the initial traveling wave head collected at the head end, the tail end and the tail end of each branch line of the main feeder line to obtain a second reference time characteristic matrix of

S102: and after the actual fault occurs, constructing a first fault time characteristic matrix and a second fault time characteristic matrix.

And elements in the first fault time characteristic matrix are respectively used for representing the actual fault traveling wave arrival time difference corresponding to the first tail end and the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line. The first end is any one of a head end of a main feeder line, a tail end of the main feeder line and a tail end of each branch line.

And elements in the second fault time characteristic matrix are respectively used for representing the actual fault traveling wave arrival time difference corresponding to a second terminal and the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line, and the second terminal is one of the head end of the main feeder line, the tail end of the main feeder line and the tail end of each branch line except the first terminal.

Specifically, two ways of constructing the reference time feature matrix before S102 correspond to the two ways, respectively, and after the actual fault occurs, the following two ways may be adopted to construct the fault time feature matrix:

the first method is as follows: main feeder (for clarity of description, main feeders below refer to actual main feeders) end-to-end.

Corresponding to the first method before S102, after an actual fault occurs, in this step, a first fault time feature matrix and a second fault time feature matrix are constructed, which may specifically adopt the following method:

and after the actual fault occurs, acquiring the actual fault traveling wave arrival time corresponding to the head end of the main feed line, the tail end of the main feed line and the tail end of each branch line. And respectively calculating the time difference between the actual fault traveling wave arrival time recorded at the tail end of the main feeder line and the actual fault traveling wave arrival time recorded at the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line, and sequencing the obtained multiple time differences according to the preset sequence to form a first fault time characteristic matrix.

For example, after an actual fault occurs, the fault time t detected by the traveling wave collecting device at the k end of the main feeder line_fnThe time t of fault traveling wave detected from the head end and the tail end of the main feeder line and the branch line_fiObtaining a first fault time characteristic matrix by time difference

Next, a second failure time feature matrix is constructed:

For example, after an actual fault occurs, the fault initial traveling wave reaching time t calibrated by the main feeder line k head end traveling wave acquisition device_f1The arrival time t of the fault initial traveling wave calibrated by other traveling wave collecting devices corresponding to the tail end of the main feeder line and the tail ends of the branch lines_fiTo obtain a second failure time characteristic matrix

The second method comprises the following steps: and correspondingly selecting two tail ends to construct a fault time characteristic matrix.

Corresponding to the two selected ends in the second mode before S102, in this step, the two selected ends should be consistent with the two selected ends, i.e., the ith end is also selected as the first end, and the mth end is selected as the second end.

The arrival time of the actual fault initial traveling wave collected at the ith tail end is t_fiThe arrival time of the actual fault initial traveling wave collected at the mth tail end is t_fmAnd constructing a first fault time characteristic matrix as follows:

the constructed second failure time characteristic matrix is as follows:

s103: and reading a first reference time characteristic matrix and a second reference time characteristic matrix which are prestored.

I.e. reading the corresponding reference time signature matrix constructed in advance for the simulated fault. As described above, the elements in the first reference time characteristic matrix are respectively used to represent arrival time differences of the simulated fault traveling wave corresponding to the first end and the head end of the main feeder line, the ends of each branch line, and the end of the main feeder line; and elements in the second reference time characteristic matrix are respectively used for representing the arrival time difference of the simulated fault traveling wave corresponding to the second tail end and the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line.

S104: and performing primary fitting respectively aiming at the first reference time characteristic matrix and the first fault time characteristic matrix, and the second reference time characteristic matrix and the second fault time characteristic matrix by adopting a least square method.

Specifically, in actual operation, the traveling wave acquisition device can be influenced by factors such as interference, lightning stroke or high-frequency noise, so that errors of different degrees appear in the calibration of the initial traveling wave head.

In the embodiment of the present application, a least square method is introduced, so that an optimal function matching for the known traveling wave collected data can be found under a minimum error condition, a first fitting relationship needs to be found, where a first reference time feature matrix and a first failure time feature matrix are matched with a linear function of a straight line Y ═ a + BX, and a second reference time feature matrix and a second failure time feature matrix are matched with a linear function of a straight line Y ═ a + BX, which specifically refers to the following formula:

wherein,

is x_i、y_iArithmetic mean of (1), x_i、y_iThe ith element in the reference time characteristic matrix and the ith element in the fault time characteristic matrix are respectively.

In the formula, B represents a slope offset degree, and a represents a displacement offset degree.

Through the steps, the element values in the reference time characteristic matrix and the fault time characteristic matrix are calculated, A and B can be obtained as long as the element values are substituted into the formula for fitting, the set fitting curve is y ═ Bx + A, and the branch node corresponding to the element on the fitting curve is the non-fault branch node.

Specifically, corresponding to the first mode and the second mode in S102, the following two modes may be adopted for performing the first fitting by using the least square method:

the first method is as follows:

the first reference time characteristic matrix

And a first failure time feature matrix

Performing linear function matching with the straight line Y, A and BX to obtain a first reference time characteristic matrix

And a first failure time feature matrix

A plurality of elements satisfying a one-time fitting relationship;

second reference time feature matrix

And a second failure time feature matrix

Performing linear function matching with the straight line Y, A and BX to obtain a second reference time characteristic matrix

And a second failure time feature matrix

A plurality of elements satisfying a one-time fitting relationship.

The second method comprises the following steps:

the first reference time characteristic matrix

And a first failure time feature matrix

And a first failure time feature matrix

A plurality of elements satisfying a one-time fitting relationship;

second reference time feature matrix

And a second failure time feature matrix

And a second failure time feature matrix

A plurality of elements satisfying a one-time fitting relationship.

S105: and determining non-fault nodes according to the fitting result, and determining the regions corresponding to the branch nodes except the non-fault branch nodes in all the branch nodes as fault candidate regions.

The branch node corresponding to the element satisfying the one-time fitting relationship is a branch node corresponding to the tail end of a branch line or the head end and the tail end of the main feeder line corresponding to the element.

For example, taking the local topology network shown in fig. 2 as an example, after performing first fitting by a least square method, assuming that two obtained elements are the 7 th element and the 8 th element in the matrix, the two elements respectively represent traveling wave arrival time differences corresponding to branch line ends 7# and 8#, the two elements correspond to branch line ends 7# and 8#, and branch nodes corresponding to 7# and 8# are g, so g is determined to be a non-faulty branch node.

In the embodiment of the present application, the branch node corresponding to the branch line end refers to the closest branch node connected to the branch line end, for example, the branch nodes corresponding to the branch line ends 4#, 5# are e, and the branch node corresponding to the branch line end 6# is d.

As an implementable manner, after each branch node is determined in S101, a branch node set may be established, and each branch node may be added to the branch node set.

In step S105, determining, as a candidate fault region, a region corresponding to a branch node other than the non-faulty branch node in the branch nodes, may specifically include:

adding the non-fault branch nodes determined by fitting the first reference time characteristic matrix and the first fault time characteristic matrix into a first non-fault branch node set, and adding the non-fault branch nodes determined by fitting the second reference time characteristic matrix and the second fault time characteristic matrix into a second non-fault branch node set; merging the first set of non-failed branch nodes and the second set of non-failed branch nodes into a set of non-failed branch nodes.

Then, a complement of the non-fault branch node set is obtained from the branch node set, and a region corresponding to a branch node in the complement is used as a fault candidate region.

For example, assuming that the branch node set is C, (a, b, C, d, e, g), assuming that the non-faulty branch nodes determined by the first reference time feature matrix and the first fault time feature matrix are a and b, the first non-faulty branch node set is NF1, (a, b), the non-faulty branch nodes determined by the second reference time feature matrix and the second fault time feature matrix are g, the second non-faulty branch node set is NF2, (g), the non-faulty branch node set is NF1 ∪ NF2, (a, b, g), and the candidate fault point set is H, the candidate fault point set is a complement of NF in C, and H is C_∪(NF)＝(c,d,e)。

In the embodiment of the present application, referring to fig. 3, after determining the failure candidate region, the method further includes:

if the complementary set is an empty set, determining that the main feeder line has a fault, calculating a distance between each branch node in the first non-fault branch node set and each branch node in the second non-fault branch node set, for example, calculating a distance between two branch nodes a and b in the set NF1 and a branch node g in the set NF2, and determining the main feeder line between the two closest branch nodes as a fault section. Where distance here refers to the length of the main feeder line between two branch nodes.

That is, when the candidate fault point set H is an empty set, it is indicated as a main feeder fault, the association degree of the elements in the set NF is set to be indicated by distance, the closer the distance is, the smaller the association is, and the main feeder interval between the two branch nodes with the minimum association degree in the set NF1 and the set NF2 is taken to be determined as a fault interval. For example, referring to fig. 4, it is calculated that the two branch nodes with the smallest relevance are b and c, and the main feeder interval between the branch nodes b and c is determined as a fault interval.

If the supplement set has only one branch node, judging that a single branch line fault occurs, and determining the branch line corresponding to the branch node as a fault branch. That is, when there is only one branch node in the candidate fault point set H, it indicates that the fault occurs in the single branch line, and the branch where the branch node is located is the faulty branch. For example, referring to fig. 5, assuming that the candidate fault point set H is (b) and includes only one branch node b, the branch line b-3 where the branch node b is located is a faulty branch.

If a plurality of branch nodes exist in the complementary set, judging that a multi-branch line fault occurs, marking the branch nodes positioned on a main feeder line in the complementary set as main branch nodes, acquiring a topology structure diagram of the distribution network in the positioning range, deleting the non-fault branch nodes, the branch lines corresponding to the non-fault branch nodes, the main feeder line tail ends and the main feeder line intervals between the main feeder line tail ends and the main branch nodes in the topology structure diagram, and reserving the main feeder line intervals between the main feeder line head ends and the main branch nodes and the multi-branch lines corresponding to the branch nodes to form a new topology structure network.

Specifically, when a plurality of branch nodes exist in the candidate fault point set H, which indicates that a multi-branch line has a fault, it is determined first through which branch node an initial traveling wave flows into the main feeder, and then a new fault domain network is formed by using the first-end substation 1# and the branches where the branch nodes are located.

For example, taking the topology shown in fig. 2 as an example, assuming that the determined candidate fault point set H is (c, d, e), and the branch node located on the main feeder is c, then c is defined as a main branch node, the head end 1# of the main feeder and the branch node c are connected, the branch line where c, d, e are located is reserved, and the rest of the lines are deleted, so that the obtained new fault domain network is shown in fig. 6.

Based on the new fault domain network, the steps of S101-S105 are executed to further narrow the fault candidate area, and if the further narrowed fault candidate area still contains a plurality of branch nodes, S101-S105 are repeatedly executed until the candidate fault point set H has only one branch node, and a final unique fault branch or fault section is determined.

Wherein, repeatedly executing S101-S105, referring to S01-S105, but not completely repeating, for example, when reconstructing a reference time feature matrix and a failure time feature matrix corresponding to a new failure domain network, constructing a third reference time feature matrix and a fourth reference time feature matrix corresponding to the reference time feature matrix and the failure time feature matrix, and then performing a fitting operation on the third reference time feature matrix and the third failure time feature matrix, and the fourth reference time feature matrix and the fourth failure time feature matrix respectively by using a least square method, and then performing a fitting operation on branch nodes corresponding to elements of the third reference time feature matrix and the third failure time feature matrix that satisfy a fitting relationship, and branch nodes corresponding to elements of the fourth reference time feature matrix and the fourth failure time feature matrix that satisfy a fitting relationship, determining the branch nodes as non-fault branch nodes, and determining areas corresponding to the branch nodes except the non-fault branch nodes in all the branch nodes included in the next fault candidate area as the next fault candidate area; if the next fault candidate area contains a plurality of branch nodes, in the same way, a loop from determining the head end of the main feeder line, the tail end of each branch line and each branch node to determining the fault candidate area is executed until only one branch line is contained in the fault candidate area.

Specifically, according to the double-end fault traveling wave positioning principle, the distance between a specific fault occurrence point and the tail end i # of the branch line is calculated:

in the formula t_i、t_jThe accurate time for the initial fault traveling wave to reach the traveling wave collecting devices installed at the tail ends i # and j # of the branch line; l_ijThe line distance from the branch line terminal i # to the branch line terminal j #; v is the traveling wave propagation velocity.

A simulation example is listed below to further explain the power distribution network fault location method in the embodiment of the present application:

taking the local topology structure of the power distribution network shown in fig. 2 as an example, simulation is performed in the PSCAD simulation software. F setting fault on branch line d-6 of main feeder 1₃And 6#200m from the end of the branch line.

Taking the head end of a main feeder line 1 as a first tail end and the tail end of the main feeder line 1 as a second tail end, firstly setting a fault of the head end of the main feeder line, and constructing a head end reference time characteristic matrix; setting a main feeder terminal fault, and constructing a terminal reference time characteristic matrix (in the embodiment of the application, the element units in the matrix are us unless specifically stated):

after the fault occurs, the traveling wave acquisition modules installed at the head end of the main feeder line, the tail end of the main feeder line and the tail end of the branch line detect the wave head of the initial fault traveling wave, and the head end and tail end fault time characteristic matrix of the main feeder line after the fault is constructed by utilizing the arrival time of the acquired initial traveling wave:

in order to further define the fault section, the least square method model is utilized to respectively perform primary fitting on the time characteristic matrixes of the head end and the tail end of the main feeder line 1.

As shown in FIG. 7, head end reference time feature matrix [ S ]₁ ^I]With head end fault time feature matrix F₁ ^I]In the method, elements corresponding to all branch nodes behind the branch node c satisfy a first-order fitting relationship, and the set NF1 ═ g](ii) a As shown in FIG. 8, the end reference time feature matrix [ S ]₁ ^II]And end-of-line fault time feature matrix [ F ]₁ ^II]In the method, the elements corresponding to all branch nodes in front of the branch node c satisfy a first-order fitting relationship, and the set NF2 ═ a, b]The complementary set of the union of NF1 set and NF2 set is used to obtain H ═ c, d, e]Fault section (i.e. fault)Barrier candidate area) will be located on the branch line where the branch node c, d, e is located.

In order to further determine the only fault branch, a new fault domain network is constructed by the node branch line in H and the main feeder head end 1#, as shown in fig. 6, only nodes c, d, e in the fault domain network form a node complete set, and the new head end reference time characteristic matrix (third reference time characteristic matrix), the new tail end reference time characteristic matrix (fourth reference time characteristic matrix), the new head end fault time characteristic matrix (third fault time characteristic matrix), and the new tail end fault time characteristic matrix (fourth fault time characteristic matrix) are respectively:

are respectively aligned to matrix [ S'₁ ^I]And [ F'₁ ^I]And [ S'₁ ^II]And [ F'₁ ^II]The first fitting was performed to obtain a set NF 1' ═ e as shown in fig. 9 and 10]The set NF 2' ═ c]H' ═ d can be obtained]Thus, the faulty section is determined to be d-6.

Finally, according to the principle of proximity, selecting a traveling wave collecting device at the tail end 6# of the branch where the fault point is located and traveling wave collecting devices corresponding to the tail ends 4# and 5# of the two branch lines connected with the branch node at the other end of the fault point, pairing the traveling wave collecting devices pairwise, calculating fault distances L6-f-4 and L6-f-5 according to the double-end fault traveling wave positioning principle, and taking the mean value of the fault distances as a final positioning result L^*6-f, and further converting the position into an accurate fault point position by taking the head end of the main feeder line 1 as a reference end. The final fault location result can be obtained: at branch d-6, distance of 234m from branch line end 6#, absolute error: 34 m.

Based on the same inventive concept, referring to fig. 11, an embodiment of the present application further provides a power distribution network fault location device, including:

a determining unit 1101, configured to determine a head end of a main feeder, a tail end of the main feeder, tail ends of branch lines, and branch nodes of a distribution network within a positioning range;

a constructing unit 1102, configured to construct a first failure time feature matrix and a second failure time feature matrix after an actual failure occurs; the elements in the first fault time characteristic matrix are respectively used for representing the actual fault traveling wave arrival time differences corresponding to a first end and a main feeder line head end, each branch line tail end and a main feeder line tail end, and the first end is any one of the main feeder line head end, the main feeder line tail end and each branch line tail end; elements in the second fault time characteristic matrix are respectively used for representing actual fault traveling wave arrival time differences corresponding to a second tail end and the head end of the main feeder line, the tail ends of all branch lines and the tail end of the main feeder line, wherein the second tail end is any one of the head end of the main feeder line, the tail end of the main feeder line and the tail end of all branch lines except the first tail end;

a fitting unit 1103, configured to read a pre-stored first reference time feature matrix and a second reference time feature matrix; the elements in the first reference time characteristic matrix are respectively used for representing the arrival time difference of the simulated fault traveling wave corresponding to the first tail end and the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line; elements in the second reference time characteristic matrix are respectively used for representing the arrival time difference of the simulated fault traveling wave corresponding to the second tail end and the head end of the main feeder line, the tail end of each branch line and the tail end of the main feeder line; performing primary fitting on the first reference time characteristic matrix and the first fault time characteristic matrix, and the second reference time characteristic matrix and the second fault time characteristic matrix respectively by adopting a least square method;

a failure removing unit 1104, configured to determine, as a non-failure branch node, a branch node corresponding to an element that satisfies a first-order fitting relationship in the first reference time feature matrix and the first failure time feature matrix, and a branch node corresponding to an element that satisfies a first-order fitting relationship in the second reference time feature matrix and the second failure time feature matrix, and determine, as a failure candidate region, a region corresponding to a branch node other than the non-failure branch node in each branch node.

Optionally, after the actual fault occurs and before the first fault time characteristic matrix and the second fault time characteristic matrix are constructed, the constructing unit 1102 is further configured to:

after an actual fault occurs, a first fault time characteristic matrix and a second fault time characteristic matrix are constructed, where the constructing unit 1102 is specifically configured to:

After determining each branch node, before determining, as a candidate fault region, a region corresponding to a branch node other than the non-faulty branch node in the branch nodes, the determining unit 1101 is further configured to:

when determining, as a candidate failure region, a region corresponding to a branch node other than the non-failure branch node in the branch nodes, the determining unit 1101 is specifically configured to:

after determining, as a candidate failure region, a region corresponding to a branch node other than the non-failed branch node among the branch nodes, the failure removal unit 1104 is further configured to:

if the complementary set is an empty set, determining that a main feeder line has a fault, calculating the distance between each branch node in the first non-fault branch node set and each branch node in the second non-fault branch node set, and determining the main feeder line between the two closest branch nodes as a fault section;

Based on the same inventive concept, referring to fig. 12, an embodiment of the present application further provides a server, including: a memory 1201, a processor 1202, wherein,

the memory 1201 is used for storing executable instructions;

the processor 1202 is configured to read and execute executable instructions stored in the memory to implement the method according to any of the above embodiments.

Compared with the prior art, the invention can achieve the following technical effects:

in the embodiment of the application, a corresponding reference time characteristic matrix and a corresponding fault time characteristic matrix are constructed only according to the obtained traveling wave arrival time difference at the tail end of the line, a least square method is adopted to perform one-time fitting to eliminate error influence, a non-fault branch node is determined according to a fitting result, a candidate fault point is further obtained, the steps can be repeated according to the candidate fault point to further reduce the range of the fault point until a fault single branch is determined, and after the fault single branch is determined, the accurate fault point position is further determined through a double-end positioning method. The positioning method is small in data processing amount, high in positioning accuracy, easy to implement and high in practicability.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may 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 flow or flows and/or block diagram block or blocks.

The embodiments of the present application have been presented for purposes of illustration and description, and are not intended to be exhaustive or limited to the application in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiment was chosen and described in order to best explain the principles of the application and the practical application, and to enable others of ordinary skill in the art to understand the application for various embodiments with various modifications as are suited to the particular use contemplated.

Claims

1. A power distribution network fault positioning method is characterized by comprising the following steps:

2. The method of claim 1, wherein after the actual failure occurs, before constructing the first failure time feature matrix and the second failure time feature matrix, further comprising:

3. The method according to claim 1, wherein after determining each branch node, before determining an area corresponding to a branch node other than the non-faulty branch node in the each branch node as a faulty candidate area, further comprising:

4. The method according to claim 3, wherein after determining, as a candidate failure region, a region corresponding to a branch node other than the non-failed branch node among the branch nodes, the method further comprises:

5. The method of claim 4, wherein after constructing the next failure candidate region, further comprising:

6. The method according to any one of claims 1 to 5, wherein after determining, as a candidate failure region, a region corresponding to a branch node other than the non-failed branch node among the branch nodes, the method further comprises:

7. A distribution network fault locating device, characterized by includes:

8. The apparatus according to claim 7, wherein after the actual failure occurs and before the first failure time feature matrix and the second failure time feature matrix are constructed, the constructing unit is further configured to:

9. The apparatus according to claim 7, wherein after determining each branch node, before determining an area corresponding to a branch node other than the non-faulty branch node among the branch nodes as a faulty candidate area, the determining unit is further configured to:

10. A server, comprising: a memory, a processor, wherein,

the memory to store executable instructions;

the processor is configured to read and execute executable instructions stored in the memory to implement the method of any one of claims 1-6.