CN113988127A - Power distribution network fault positioning method and device, electronic equipment and storage medium - Google Patents
Power distribution network fault positioning method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN113988127A CN113988127A CN202111248570.9A CN202111248570A CN113988127A CN 113988127 A CN113988127 A CN 113988127A CN 202111248570 A CN202111248570 A CN 202111248570A CN 113988127 A CN113988127 A CN 113988127A
- Authority
- CN
- China
- Prior art keywords
- fault
- traveling wave
- time
- sample
- frequency matrix
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 56
- 238000009826 distribution Methods 0.000 title claims abstract description 54
- 238000003860 storage Methods 0.000 title claims abstract description 13
- 239000011159 matrix material Substances 0.000 claims abstract description 133
- 230000001052 transient effect Effects 0.000 claims abstract description 101
- 238000005070 sampling Methods 0.000 claims abstract description 28
- 230000009466 transformation Effects 0.000 claims description 16
- 238000004364 calculation method Methods 0.000 claims description 11
- 238000006243 chemical reaction Methods 0.000 claims description 8
- 238000000354 decomposition reaction Methods 0.000 claims description 7
- 238000010586 diagram Methods 0.000 description 11
- 238000004590 computer program Methods 0.000 description 7
- 230000008569 process Effects 0.000 description 7
- 230000005540 biological transmission Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 238000005314 correlation function Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
- 239000013598 vector Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Economics (AREA)
- Health & Medical Sciences (AREA)
- Data Mining & Analysis (AREA)
- Artificial Intelligence (AREA)
- General Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Signal Processing (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Public Health (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Water Supply & Treatment (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Locating Faults (AREA)
Abstract
The invention discloses a power distribution network fault positioning method and device, electronic equipment and a storage medium, which are used for solving the technical problem of inaccurate power distribution network fault positioning. The invention comprises the following steps: dividing branch lines to obtain a plurality of sections, and setting simulated fault points at the joints of adjacent sections; collecting the traveling wave signal reflected by each simulated fault point through a traveling wave collecting device, and generating a sample fault time-frequency matrix of each simulated fault point by adopting the corresponding traveling wave signal; sampling the transient signal, and calculating an actual fault time-frequency matrix of the transient signal; calculating the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix; and determining a fault point according to the similarity.
Description
Technical Field
The invention relates to the technical field of fault location, in particular to a power distribution network fault location method and device, electronic equipment and a storage medium.
Background
The traditional power distribution network fault location method has the advantages that the traveling wave method is not influenced by factors such as system parameters, transition resistance and system operation modes, and is widely applied. The traveling wave method can be divided into a single-end method and a multi-end method in principle. The single-end method mainly utilizes the refraction/reflection characteristics of traveling waves to realize fault positioning according to the time difference between the initial traveling wave head and the first reflected wave head from a fault point, and the single-end method positioning device is simple and easy to realize. Meanwhile, the calibration of the time-domain traveling wave head can be realized by a derivative method, a cross-correlation function method, a waveform curve fitting method and the like. The double-end method measures the fault distance according to the time difference of the initial traveling wave reaching the two ends of the line, only needs to capture the first reaching wave head, is easy to identify and has high positioning precision.
However, the wave head distortion is complex under the condition of power distribution network faults, and interference signals are easy to mix, so that the accurate determination and reliability of the time domain traveling wave head calibration are not high in the ways of a derivative method, a cross-correlation function method, a waveform curve fitting method and the like, and particularly in a power distribution network with a complex topological structure, the wave head source is more difficult to distinguish; the double-end method requires the detection devices to be arranged at the branch nodes, has strict requirements on clock synchronization and greatly increases the ranging cost.
Disclosure of Invention
The invention provides a power distribution network fault positioning method and device, electronic equipment and a storage medium, which are used for solving the technical problem of inaccurate power distribution network fault positioning.
The invention provides a fault positioning method for a power distribution network, wherein the power distribution network is provided with a plurality of branch lines; a traveling wave acquisition device is arranged at the outlet of the power distribution network; the method comprises the following steps:
dividing the branch line to obtain a plurality of sections, and setting simulated fault points at the connection positions of adjacent sections;
collecting the traveling wave signal reflected by each simulated fault point through the traveling wave collecting device, and generating a sample fault time-frequency matrix of each simulated fault point by adopting the corresponding traveling wave signal;
sampling transient signals, and calculating an actual fault time-frequency matrix of the transient signals;
calculating the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix;
and determining a fault point according to the similarity.
Optionally, the step of acquiring, by the traveling wave acquisition device, the traveling wave signal reflected by each simulated fault point, and generating a sample fault time-frequency matrix of each simulated fault point by using the corresponding traveling wave signal includes:
collecting traveling wave signals reflected by each simulated fault point through a traveling wave collecting device;
intercepting a target traveling wave signal of a preset time window from the traveling wave signal;
and performing time-frequency decomposition on the target traveling wave signal to obtain a sample fault time-frequency matrix.
Optionally, the step of sampling the transient signal and calculating an actual failure time-frequency matrix of the transient signal includes:
sampling a transient signal, and performing discrete S conversion on the transient signal to obtain a conversion matrix;
and calculating an actual fault time-frequency matrix of the transient signal according to the transformation matrix.
Optionally, the step of determining a fault point according to the similarity includes:
taking a simulated fault point corresponding to the sample fault time-frequency matrix with the maximum similarity to the actual fault time-frequency matrix as a sample fault point, and acquiring a sample fault transient waveform corresponding to the sample fault point;
acquiring two adjacent fault points of the sample fault points, and acquiring adjacent fault transient waveforms corresponding to the adjacent fault points;
acquiring an actual fault transient waveform of the transient signal;
calculating a first overall amplitude deviation between the actual fault transient waveform and the sample fault transient waveform;
calculating a second overall amplitude deviation between the actual fault transient waveform and the adjacent fault transient waveform;
determining a fault interval by using the first integral amplitude deviation and the second integral amplitude deviation;
and determining a fault point in the fault section.
The invention also provides a fault positioning device for the power distribution network, wherein the power distribution network is provided with a plurality of branch lines; a traveling wave acquisition device is arranged at the outlet of the power distribution network; the device comprises:
the simulated fault point setting module is used for dividing the branch line to obtain a plurality of sections and setting simulated fault points at the connection positions of adjacent sections;
the sample fault time-frequency matrix generation module is used for acquiring the traveling wave signals reflected by each simulated fault point through the traveling wave acquisition device and generating the sample fault time-frequency matrix of each simulated fault point by adopting the corresponding traveling wave signals;
the actual fault time-frequency matrix generation module is used for sampling the transient signals and calculating the actual fault time-frequency matrix of the transient signals;
the similarity calculation module is used for calculating the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix;
and the fault point determining module is used for determining a fault point according to the similarity.
Optionally, the sample failure time-frequency matrix generating module includes:
the traveling wave signal acquisition submodule is used for acquiring the traveling wave signal reflected by each simulated fault point through the traveling wave acquisition device;
the target traveling wave signal intercepting submodule is used for intercepting a target traveling wave signal of a preset time window from the traveling wave signal;
and the sample fault time-frequency matrix generation submodule is used for performing time-frequency decomposition on the target travelling wave signal to obtain a sample fault time-frequency matrix.
Optionally, the actual fault time-frequency matrix generating module includes:
the transformation matrix generation submodule is used for sampling the transient signal and performing discrete S transformation on the transient signal to obtain a transformation matrix;
and the actual fault time-frequency matrix generation submodule is used for calculating the actual fault time-frequency matrix of the transient signal according to the transformation matrix.
Optionally, the failure point determining module includes:
the sample fault point determining submodule is used for taking a simulated fault point corresponding to the sample fault time-frequency matrix with the maximum similarity to the actual fault time-frequency matrix as a sample fault point and acquiring a sample fault transient waveform corresponding to the sample fault point;
the adjacent fault point acquisition submodule is used for acquiring two adjacent fault points of the sample fault point and acquiring adjacent fault transient waveforms corresponding to the adjacent fault points;
an actual fault transient waveform acquisition submodule for acquiring an actual fault transient waveform of the transient signal;
a first integral amplitude deviation calculation submodule for calculating a first integral amplitude deviation between the actual fault transient waveform and the sample fault transient waveform;
a second integral amplitude deviation calculation submodule for calculating a second integral amplitude deviation between the actual fault transient waveform and the adjacent fault transient waveform;
the fault interval determining submodule is used for determining a fault interval by adopting the first integral amplitude deviation and the second integral amplitude deviation;
and the fault point determining submodule is used for determining a fault point in the fault section.
The invention also provides an electronic device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the power distribution network fault location method according to instructions in the program code.
The invention also provides a computer-readable storage medium for storing program code for executing the power distribution network fault location method according to any one of the above.
According to the technical scheme, the invention has the following advantages: the method comprises the steps of dividing branch lines to obtain a plurality of sections, and setting simulated fault points at the joints of adjacent sections; collecting the traveling wave signal reflected by each simulated fault point through a traveling wave collecting device, and generating a sample fault time-frequency matrix of each simulated fault point by adopting the corresponding traveling wave signal; sampling the transient signal, and calculating an actual fault time-frequency matrix of the transient signal; calculating the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix; and determining a fault point according to the similarity. The technical problem of inaccurate fault location of the power distribution network is solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a flowchart illustrating steps of a method for locating a fault in a power distribution network according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating steps of a method for locating a fault in a power distribution network according to another embodiment of the present invention;
FIG. 3 is a schematic diagram of the location of a fault point on a branch line;
fig. 4 is a block diagram of a power distribution network fault location device according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a power distribution network fault positioning method and device, electronic equipment and a storage medium, which are used for solving the technical problem of inaccurate power distribution network fault positioning.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart illustrating steps of a power distribution network fault location method according to an embodiment of the present invention.
The invention provides a fault positioning method for a power distribution network, wherein the power distribution network is provided with a plurality of branch lines; a traveling wave acquisition device is arranged at the outlet of the power distribution network; the method may specifically comprise the steps of:
the distribution network is an electric power network which receives electric energy from a transmission network or a regional power plant and distributes the electric energy to various users on site through distribution facilities or step by step according to voltage. The power distribution network consists of overhead lines, cables, towers, distribution transformers, isolating switches, reactive power compensators, accessory facilities and the like, and plays a role in distributing electric energy in a power network.
Travelling wave, refers to a state of transmission of a plane wave on a transmission line, the amplitude of which varies exponentially along the direction of propagation, and the phase varies linearly along the transmission line.
The traveling wave acquisition device is a device for acquiring traveling wave signals.
In the embodiment of the invention, each branch line of the power distribution network can be divided into a plurality of sections according to two line types of an overhead line and a cable, and 1 simulated fault point is arranged at the joint of every two adjacent sections; in addition, an observation point can be arranged at the wire outlet of the power distribution network, and a traveling wave acquisition device is arranged at the observation point and is used for acquiring traveling wave signals reflected by the fault point.
in the embodiment of the invention, the traveling wave acquisition device can acquire the traveling wave signal of each simulated fault point and generate the sample fault time-frequency matrix of each simulated fault point by adopting the corresponding traveling wave signal. Further, a branch waveform database of each branch line may be generated according to the sample fault time-frequency matrix of each simulated fault point in each branch line.
when fault location is actually carried out, transient signals in the power distribution network can be sampled, and a corresponding actual fault time-frequency matrix is calculated. And determining a fault point by combining the sample fault time-frequency matrix.
104, calculating the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix;
and 105, determining a fault point according to the similarity.
In the embodiment of the invention, the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix can be calculated to determine the fault point.
The method comprises the steps of dividing branch lines to obtain a plurality of sections, and setting simulated fault points at the joints of adjacent sections; collecting the traveling wave signal reflected by each simulated fault point through a traveling wave collecting device, and generating a sample fault time-frequency matrix of each simulated fault point by adopting the corresponding traveling wave signal; sampling the transient signal, and calculating an actual fault time-frequency matrix of the transient signal; calculating the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix; and determining a fault point according to the similarity. The technical problem of inaccurate fault location of the power distribution network is solved.
Referring to fig. 2, fig. 2 is a flowchart illustrating a method for locating a fault of a power distribution network according to another embodiment of the present invention.
in the embodiment of the invention, each branch line of the power distribution network can be divided into a plurality of sections according to two line types of an overhead line and a cable, and 1 simulated fault point is arranged at the joint of every two adjacent sections; in addition, an observation point can be arranged at the wire outlet of the power distribution network, and a traveling wave acquisition device is arranged at the observation point and is used for acquiring traveling wave signals reflected by the fault point.
in the embodiment of the present invention, the traveling wave signal acquired by the traveling wave acquisition device may be intercepted to obtain a target traveling wave signal of a preset time window, and the target traveling wave signal of the preset time window may be subjected to time-frequency division decomposition by using discrete S transform to obtain a sample fault time-frequency matrix.
Specifically, generating the sample failure time-frequency matrix may be implemented by:
collecting traveling wave signals within a certain time, and carrying out one-dimensional continuous S conversion on the original continuous traveling wave signals x (t) to obtain
In the formula, w (tau-t, f) is a Gaussian window, the parameter of the position of the Gaussian window at the time t axis is tau, and the frequency is f. The S-transformed signal S (τ, f) is reduced by inverse transformation to a signal x (t), with the inverse of S being represented as:
and (3) realizing the discretization operation of the S transform by utilizing the fast Fourier transform. Discretizing x (t), and making t be kT to obtain a discrete time sequence x (kT), wherein the discrete time sequence x (kT) has a discrete Fourier transform expression as follows:
wherein k is a sampling time interval, k is 0,1,2 …, N-1; n is a frequency parameter, and N is 0,1,2 …, N-1; t is a sampling time interval; and N is the number of sampling points.
Then, let τ → jT, f → n/NT based on the discrete Fourier expression of x (kT), and obtain the one-dimensional discrete S transform of x (kT) by Fourier transform calculation as follows:
in the formula: i is an imaginary unit; j is a time parameter, j is 0,1,2 …, N-1; n is a frequency parameter, N is 1,2 …, N-1; m represents the number of frequencies for decomposing the discrete signal, and N is 1,2 …, N-1. The discrete S transform when the frequency parameter n is 0 is defined as:
by performing a discrete S transform on the discrete time series x (kt) of the traveling wave signal of the sampling point, a complex matrix is obtained as follows:
in the formula: the elements S (a, b) of the matrix S represent the b-th sampling point at the a-th frequency, the row elements of the matrix corresponding to the frequency of the signal and the column elements of the matrix corresponding to the time points at which the signal is sampled. The frequency difference between two adjacent rows is:
the frequency of row a is:
in the formula: f. ofsIs the sampling frequency.
In the formula, the amplitude vectors at each frequency obtained after S conversion are classified and integrated. N sampling points are arranged under each frequency, the sampling points are equally divided into M blocks, and the amplitude corresponding to the g-th time period block under the a-th line frequency is defined as follows:
wherein, real () represents to get real part, and each time-frequency small block in the complex matrix is respectively solved according to the above formula, and finally, a sample failure time-frequency matrix E of the traveling wave signal is obtained as follows:
in this embodiment of the present invention, step 205 may include:
sampling the transient signal, and performing discrete S conversion on the transient signal to obtain a conversion matrix;
and calculating an actual fault time-frequency matrix of the transient signal according to the transformation matrix.
In the embodiment of the present invention, the actual fault time-frequency matrix of the transient signal may be obtained in the same manner as the sample fault time-frequency matrix of the simulated fault traveling wave signal is obtained. The present invention will not be described in detail.
in the embodiment of the invention, the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix can be calculated to determine the fault point.
Specifically, the similarity ρ between the actual failure time-frequency matrix and the sample failure time-frequency matrix may be defined as:
wherein A is1Is a sample failure time-frequency matrix, A2Is an actual failure time-frequency matrix.<A1，A2>Is represented by A1And A2Inner product of (d); | A1I is the matrix A1Norm of (d); | A2I is the matrix A2Norm of (d). Gamma is the matrix A1、A2The included angle between them; when γ is 90 °, ρ is 0, indicating that the two matrices are completely different; when γ is 0 °, ρ is 1, indicating that the two matrices have extremely high similarity.
The similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix can be used for judging the branch line generating the fault, and the specific judgment formula is as follows:
ρmax＞ρset
where ρ ismaxIs the maximum similarity, rho, between the actual fault time-frequency matrix and the sample fault time-frequency matrix of the simulated fault point on the branch linesetIs a fault threshold.
When rho of a branch linemaxGreater than rhosetAnd the fault occurs on the branch line.
And step 207, determining a fault point according to the similarity.
In one example, step 207 may include the following sub-steps:
s71, taking the simulated fault point corresponding to the sample fault time-frequency matrix with the maximum similarity to the actual fault time-frequency matrix as a sample fault point, and acquiring a sample fault transient waveform corresponding to the sample fault point;
s72, acquiring two adjacent fault points of the sample fault points, and acquiring adjacent fault transient waveforms corresponding to the adjacent fault points;
s73, acquiring the actual fault transient waveform of the transient signal;
s74, calculating a first integral amplitude deviation between the actual fault transient waveform and the sample fault transient waveform;
s75, calculating a second integral amplitude deviation between the actual fault transient waveform and the adjacent fault transient waveform;
s76, determining a fault interval by adopting the first integral amplitude deviation and the second integral amplitude deviation;
and S77, determining a fault point in the fault section.
Determining the simulation fault point with the maximum similarity value as a sample fault point YnAnd determining two adjacent fault points Y before and after the sample fault pointn-1And Yn+1(ii) a And acquiring a sample fault transient waveform corresponding to the sample fault point and an adjacent fault transient waveform of an adjacent fault point. Respectively calculating first integral amplitude deviation of sample fault transient waveform
Second integral amplitude deviation from two adjacent fault transient waveforms
To determine the failure zone. Wherein, the integral amplitude deviation is the sum of the amplitude deviations of each sampling point. The sample point amplitude deviation is the amplitude deviation between the two waveforms a and b at the sample point (e.g., i). The calculation process is as follows:
εi＝|ai-bi|
wherein, aiAnd biThe amplitudes of the waveform a and the waveform b at the ith sampling point are respectively.
After the first overall amplitude deviation and the second overall amplitude deviation are determined, the section between the two corresponding fault points with the minimum value in the first overall amplitude deviation and the two second overall amplitude deviations is the fault section.
For example, if
The true failure point is located at YnAnd Yn-1And is prepared fromTo YnThe distance of (a) is:
wherein,
indicating a sample failure point YnTo adjacent fault point Yn-1The distance between them.
In one example, the location of the fault point on the branch line is shown in fig. 3.
The method comprises the steps of dividing branch lines to obtain a plurality of sections, and setting simulated fault points at the joints of adjacent sections; collecting the traveling wave signal reflected by each simulated fault point through a traveling wave collecting device, and generating a sample fault time-frequency matrix of each simulated fault point by adopting the corresponding traveling wave signal; sampling the transient signal, and calculating an actual fault time-frequency matrix of the transient signal; calculating the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix; and determining a fault point according to the similarity. The technical problem of inaccurate fault location of the power distribution network is solved.
Referring to fig. 4, fig. 4 is a block diagram of a power distribution network fault location device according to an embodiment of the present invention.
The embodiment of the invention provides a power distribution network fault positioning device, wherein a power distribution network is provided with a plurality of branch lines; a traveling wave acquisition device is arranged at the outlet of the power distribution network; the device comprises:
the simulated fault point setting module 401 is configured to divide the branch line to obtain a plurality of segments, and set a simulated fault point at a connection point of adjacent segments;
a sample fault time-frequency matrix generation module 402, configured to acquire the traveling wave signal reflected by each simulated fault point through a traveling wave acquisition device, and generate a sample fault time-frequency matrix of each simulated fault point by using the corresponding traveling wave signal;
an actual fault time-frequency matrix generation module 403, configured to sample the transient signal and calculate an actual fault time-frequency matrix of the transient signal;
a similarity calculation module 404, configured to calculate a similarity between the actual failure time-frequency matrix and the sample failure time-frequency matrix;
and a failure point determining module 405, configured to determine a failure point according to the similarity.
In this embodiment of the present invention, the sample failure time-frequency matrix generating module 402 includes:
the traveling wave signal acquisition submodule is used for acquiring the traveling wave signal reflected by each simulated fault point through the traveling wave acquisition device;
the target traveling wave signal intercepting submodule is used for intercepting a target traveling wave signal of a preset time window from the traveling wave signal;
and the sample fault time-frequency matrix generation submodule is used for performing time-frequency decomposition on the target travelling wave signal to obtain a sample fault time-frequency matrix.
In this embodiment of the present invention, the actual fault time-frequency matrix generating module 403 includes:
the transformation matrix generation submodule is used for sampling the transient signal and performing discrete S transformation on the transient signal to obtain a transformation matrix;
and the actual fault time-frequency matrix generation submodule is used for calculating the actual fault time-frequency matrix of the transient signal according to the transformation matrix.
In an embodiment of the present invention, the failure point determining module includes:
the sample fault point determining submodule is used for taking a simulated fault point corresponding to a sample fault time-frequency matrix with the maximum similarity to the actual fault time-frequency matrix as a sample fault point and acquiring a sample fault transient waveform corresponding to the sample fault point;
the adjacent fault point acquisition submodule is used for acquiring two adjacent fault points of the sample fault point and acquiring adjacent fault transient waveforms corresponding to the adjacent fault points;
the actual fault transient waveform acquisition submodule is used for acquiring an actual fault transient waveform of the transient signal;
the first integral amplitude deviation calculation submodule is used for calculating a first integral amplitude deviation between the actual fault transient waveform and the sample fault transient waveform;
the second integral amplitude deviation calculation submodule is used for calculating second integral amplitude deviation between the actual fault transient waveform and the adjacent fault transient waveform;
the fault interval determining submodule is used for determining a fault interval by adopting the first integral amplitude deviation and the second integral amplitude deviation;
and the fault point determining submodule is used for determining a fault point in the fault section.
An embodiment of the present invention further provides an electronic device, where the device includes a processor and a memory:
the memory is used for storing the program codes and transmitting the program codes to the processor;
the processor is used for executing the power distribution network fault positioning method according to the embodiment of the invention according to the instructions in the program codes.
The embodiment of the invention also provides a computer-readable storage medium, which is used for storing the program codes, and the program codes are used for executing the power distribution network fault positioning method provided by the embodiment of the invention.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention 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.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. 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 terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, 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 stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function 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 terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A fault positioning method for a power distribution network is characterized in that the power distribution network is provided with a plurality of branch lines; a traveling wave acquisition device is arranged at the outlet of the power distribution network; the method comprises the following steps:
dividing the branch line to obtain a plurality of sections, and setting simulated fault points at the connection positions of adjacent sections;
collecting the traveling wave signal reflected by each simulated fault point through the traveling wave collecting device, and generating a sample fault time-frequency matrix of each simulated fault point by adopting the corresponding traveling wave signal;
sampling transient signals, and calculating an actual fault time-frequency matrix of the transient signals;
calculating the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix;
and determining a fault point according to the similarity.
2. The method according to claim 1, wherein the step of collecting the traveling wave signal reflected by each simulated fault point through the traveling wave collecting device and generating a sample fault time-frequency matrix of each simulated fault point by using the corresponding traveling wave signal comprises:
collecting traveling wave signals reflected by each simulated fault point through a traveling wave collecting device;
intercepting a target traveling wave signal of a preset time window from the traveling wave signal;
and performing time-frequency decomposition on the target traveling wave signal to obtain a sample fault time-frequency matrix.
3. The method of claim 1, wherein the step of sampling the transient signal and calculating the actual failure time-frequency matrix of the transient signal comprises:
sampling a transient signal, and performing discrete S conversion on the transient signal to obtain a conversion matrix;
and calculating an actual fault time-frequency matrix of the transient signal according to the transformation matrix.
4. The method of claim 1, wherein the step of determining a failure point based on the similarity comprises:
taking a simulated fault point corresponding to the sample fault time-frequency matrix with the maximum similarity to the actual fault time-frequency matrix as a sample fault point, and acquiring a sample fault transient waveform corresponding to the sample fault point;
acquiring two adjacent fault points of the sample fault points, and acquiring adjacent fault transient waveforms corresponding to the adjacent fault points;
acquiring an actual fault transient waveform of the transient signal;
calculating a first overall amplitude deviation between the actual fault transient waveform and the sample fault transient waveform;
calculating a second overall amplitude deviation between the actual fault transient waveform and the adjacent fault transient waveform;
determining a fault interval by using the first integral amplitude deviation and the second integral amplitude deviation;
and determining a fault point in the fault section.
5. The fault positioning device for the power distribution network is characterized in that the power distribution network is provided with a plurality of branch lines; a traveling wave acquisition device is arranged at the outlet of the power distribution network; the device comprises:
the simulated fault point setting module is used for dividing the branch line to obtain a plurality of sections and setting simulated fault points at the connection positions of adjacent sections;
the sample fault time-frequency matrix generation module is used for acquiring the traveling wave signals reflected by each simulated fault point through the traveling wave acquisition device and generating the sample fault time-frequency matrix of each simulated fault point by adopting the corresponding traveling wave signals;
the actual fault time-frequency matrix generation module is used for sampling the transient signals and calculating the actual fault time-frequency matrix of the transient signals;
the similarity calculation module is used for calculating the similarity between the actual fault time-frequency matrix and the sample fault time-frequency matrix;
and the fault point determining module is used for determining a fault point according to the similarity.
6. The apparatus of claim 5, wherein the sample failure time-frequency matrix generation module comprises:
the traveling wave signal acquisition submodule is used for acquiring the traveling wave signal reflected by each simulated fault point through the traveling wave acquisition device;
the target traveling wave signal intercepting submodule is used for intercepting a target traveling wave signal of a preset time window from the traveling wave signal;
and the sample fault time-frequency matrix generation submodule is used for performing time-frequency decomposition on the target travelling wave signal to obtain a sample fault time-frequency matrix.
7. The apparatus of claim 5, wherein the actual failure time-frequency matrix generation module comprises:
the transformation matrix generation submodule is used for sampling the transient signal and performing discrete S transformation on the transient signal to obtain a transformation matrix;
and the actual fault time-frequency matrix generation submodule is used for calculating the actual fault time-frequency matrix of the transient signal according to the transformation matrix.
8. The apparatus of claim 5, wherein the failure point determination module comprises:
the sample fault point determining submodule is used for taking a simulated fault point corresponding to the sample fault time-frequency matrix with the maximum similarity to the actual fault time-frequency matrix as a sample fault point and acquiring a sample fault transient waveform corresponding to the sample fault point;
the adjacent fault point acquisition submodule is used for acquiring two adjacent fault points of the sample fault point and acquiring adjacent fault transient waveforms corresponding to the adjacent fault points;
an actual fault transient waveform acquisition submodule for acquiring an actual fault transient waveform of the transient signal;
a first integral amplitude deviation calculation submodule for calculating a first integral amplitude deviation between the actual fault transient waveform and the sample fault transient waveform;
a second integral amplitude deviation calculation submodule for calculating a second integral amplitude deviation between the actual fault transient waveform and the adjacent fault transient waveform;
the fault interval determining submodule is used for determining a fault interval by adopting the first integral amplitude deviation and the second integral amplitude deviation;
and the fault point determining submodule is used for determining a fault point in the fault section.
9. An electronic device, comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the power distribution network fault location method according to any one of claims 1 to 4 according to instructions in the program code.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium is configured to store program code for performing the power distribution network fault location method of any of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111248570.9A CN113988127A (en) | 2021-10-26 | 2021-10-26 | Power distribution network fault positioning method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111248570.9A CN113988127A (en) | 2021-10-26 | 2021-10-26 | Power distribution network fault positioning method and device, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113988127A true CN113988127A (en) | 2022-01-28 |
Family
ID=79741706
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111248570.9A Pending CN113988127A (en) | 2021-10-26 | 2021-10-26 | Power distribution network fault positioning method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113988127A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114878971A (en) * | 2022-05-31 | 2022-08-09 | 国网北京市电力公司 | Method, device, equipment and medium for positioning fault point of power distribution network |
-
2021
- 2021-10-26 CN CN202111248570.9A patent/CN113988127A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114878971A (en) * | 2022-05-31 | 2022-08-09 | 国网北京市电力公司 | Method, device, equipment and medium for positioning fault point of power distribution network |
| CN114878971B (en) * | 2022-05-31 | 2024-01-30 | 国网北京市电力公司 | Power distribution network fault point positioning method, device, equipment and medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Xie et al. | A traveling wave-based fault location method employing VMD-TEO for distribution network | |
| Lopes et al. | Real-time traveling-wave-based fault location using two-terminal unsynchronized data | |
| CN107703418B (en) | Shelf depreciation location error compensation method based on more radial base neural nets | |
| JP7304783B2 (en) | Power system monitoring apparatus and method | |
| Dashtdar et al. | Fault location in the transmission network using artificial neural network | |
| CN109521330B (en) | Power transmission line fault traveling wave distance measurement method based on ARIMA wave head prediction | |
| CN105445624A (en) | Cable fault positioning method according to combination of wavelet transformation and curve fitting | |
| Da Silva et al. | Fault location on transmission lines using complex-domain neural networks | |
| Yang et al. | Complete elimination of DC offset in current signals for relaying applications | |
| CN110967594A (en) | Method and device for positioning faults of power distribution network containing inverter type distributed power supply | |
| Kafal et al. | An effective method based on time reversal and optimization techniques for locating faults on power grids | |
| Dardengo et al. | Single-terminal fault location in HVDC lines with accurate wave velocity estimation | |
| CN113945799A (en) | Power line network fault positioning method and device, electronic equipment and storage medium | |
| CN113988127A (en) | Power distribution network fault positioning method and device, electronic equipment and storage medium | |
| Huai et al. | Combined line fault location method for MMC–HVDC transmission systems | |
| Coban et al. | Artificial neural network based fault location on 230 kv transmission line using voltage and current signals | |
| CN111654264B (en) | Method and system for generating signal pulse sequence by signal data simulator | |
| Papadopoulos et al. | Online parameter identification and generic modeling derivation of a dynamic load model in distribution grids | |
| CN113655343A (en) | Power distribution network single-phase earth fault positioning method, device, equipment and storage medium | |
| CN112001059B (en) | Method and device for establishing broadband model of flexible direct current converter valve submodule | |
| Amin et al. | Differential equation fault location algorithm with harmonic effects in power system | |
| Bohórquez et al. | One-ended fault location method based on machine learning models | |
| CN117310374A (en) | Distance measurement method for submarine cable faults | |
| Mosavi et al. | Stability comparison of fault location techniques against faulty GPS time tagging for three-terminal lines | |
| Ali et al. | High impedance fault localization using discrete wavelet transform for single line to ground fault |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |