CN114594344A - Method and system for positioning and identifying transmission line fault - Google Patents

Method and system for positioning and identifying transmission line fault Download PDF

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Publication number
CN114594344A
CN114594344A CN202210294549.0A CN202210294549A CN114594344A CN 114594344 A CN114594344 A CN 114594344A CN 202210294549 A CN202210294549 A CN 202210294549A CN 114594344 A CN114594344 A CN 114594344A
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fault
transmission line
phase
power transmission
phasor
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刘虎林
刘中平
邱智勇
倪腊琴
叶海
桂强
韩俊
苏柏松
李雪冬
李书琦
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BEIJING JOIN BRIGHT DIGITAL POWER TECHNOLOGY CO LTD
East China Branch Of State Grid Corp ltd
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BEIJING JOIN BRIGHT DIGITAL POWER TECHNOLOGY CO LTD
East China Branch Of State Grid Corp ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08—Locating faults in cables, transmission lines, or networks
    • G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
    • G01R31/085—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution lines, e.g. overhead
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
    • G01R31/52—Testing for short-circuits, leakage current or ground faults
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
    • G01R31/54—Testing for continuity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
    • G01R31/58—Testing of lines, cables or conductors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y04S10/52—Outage or fault management, e.g. fault detection or location

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Abstract

The invention relates to the technical field of power systems, and provides a method and a system for positioning and identifying a power transmission line fault, which comprises the steps of obtaining current phasor and voltage phasor before and after the power transmission line fault of a target domain and state quantities of a circuit breaker and a relay; and carrying out fault location on the target domain power transmission line by adopting an improved breadth-first search algorithm. By the technical scheme, on the premise of kirchhoff's law of the fault line, the breadth-first search algorithm is improved, and more accurate fault location of the power transmission line can be realized.

Description

Method and system for positioning and identifying transmission line fault
Technical Field
The invention relates to the technical field of power systems, in particular to a method and a system for positioning and identifying faults of a power transmission line.
Background
Under the promotion of development and construction of energy internet and ubiquitous power internet of things, trends of regional interconnection, various energy interconnection and global interconnection of a power system are increasingly obvious, various distributed renewable energy sources, cold, heat, gas, water and the like are continuously incorporated, so that a power grid structure expands in a large range, the probability of failure of a power transmission line is increased day by day, the types of failures are increased continuously, and the difficulty of failure analysis and positioning of the power transmission line of the power system is increased more and more. Accurate and rapid analysis and positioning of power transmission line faults of a power system are the core and foundation for ensuring safe and stable operation of the power system.
At present, the transmission line fault identification is mainly carried out according to electric quantities provided by an energy management system, a data acquisition and monitoring control system and a wide area measurement system in a dispatching master station, and fault identification and positioning are carried out by establishing transmission line fault voltage, current electric quantities and switching quantities of protection equipment by using a traditional algorithm. The dependence on manual work to analyze and judge the recording data easily causes the problems of erroneous judgment, low efficiency and the like. In recent years, with the development of artificial intelligence technology, a small number of people have applied the artificial intelligence technology to power line fault identification, but the artificial intelligence technology does not relate to the multi-source data fusion problem, establish a fault model and the like, has low fault analysis and positioning effect accuracy, and is easy to misjudge.
Disclosure of Invention
The invention provides a method and a system for positioning and identifying a power transmission line fault, which solve the problems of low accuracy and easy misjudgment of analysis and positioning results of the power transmission line fault in the prior art.
The technical scheme of the invention is as follows:
in a first aspect, a method for locating and identifying a fault of a power transmission line includes the following steps:
acquiring current phasor and voltage phasor before and after all transmission line ij faults in a target area, and state quantities of circuit breakers and relays before and after the transmission line ij faults;
carrying out first fault location on the target area transmission line ij through the state quantities of the circuit breaker and the relay before and after the transmission line ij fails, and determining the transmission line with the fault;
carrying out second fault location on the power transmission line with the fault by adopting an improved breadth-first search algorithm according to the current phasor and the voltage phasor before and after the ij fault of the power transmission line, and determining the actual position of the fault;
the improved breadth-first search algorithm comprises the following steps that for any power transmission line with a fault, a breadth-first algorithm is adopted, and the processing from a first node to a terminal point is executed, wherein the first node and the terminal point are specifically as follows: when the original power flow flowing direction of the power transmission line ij flows from the node i to the node j, the node i is a first node, and the node j is a terminal point.
Further, the method also comprises a fault type identification method, wherein the fault type identification method comprises a short-circuit fault identification method and a disconnection fault identification method, and the short-circuit fault identification method comprises the following steps:
acquiring current phasor, voltage phasor and fault types before and after a power transmission line fault occurs in a source domain;
taking current phasor and voltage phasor before and after the power transmission line with the source domain fault as input, taking the fault type as output, and training a fault type identification model;
and applying the trained fault type identification model to a target area by adopting a transfer learning method, and inputting current phasor and voltage phasor before and after the fault of the power transmission line with the fault in the target area to obtain the fault type of the power transmission line with the fault in the target area.
In a second aspect, a system for analyzing and positioning transmission line faults comprises a fault positioning module, wherein the fault positioning module comprises,
the first obtaining module is used for obtaining current phasor and voltage phasor before and after the failure of all transmission lines ij in a target area, and state quantities of circuit breakers and relays before and after the failure of the transmission lines ij;
the first positioning module is used for carrying out first fault positioning on the target area transmission line ij through the state quantities of the circuit breaker and the relay before and after the transmission line ij fails, and determining the transmission line with the fault;
and the second positioning module is used for performing second fault positioning on the power transmission line with the fault by adopting an improved breadth-first search algorithm through the current phasor and the voltage phasor before and after the fault of the power transmission line ij, and determining the actual position of the fault.
Further, the system also comprises a fault type identification module which comprises,
the second obtaining module is used for obtaining current phasor, voltage phasor, state quantities of a circuit breaker and a relay and fault types before and after the source domain power transmission line is in fault;
the first training module is used for taking current phasor and voltage phasor before and after the source domain power transmission line fault and state quantities of a circuit breaker and a relay as input, taking the source domain power transmission line fault type as output and training a fault type identification model;
and the first processing module is used for applying the trained fault type identification model to a target domain by adopting a transfer learning method, and inputting current phasor and voltage phasor before and after the fault of the power transmission line of the target domain and state quantities of a circuit breaker and a relay to obtain the fault type of the power transmission line.
In a third aspect, a computer-readable storage medium has stored therein a computer program, which when executed by a processor implements the steps of the method for locating and identifying a power transmission line fault.
The working principle and the beneficial effects of the invention are as follows:
1. the invention provides a method and a system for positioning and identifying transmission line faults, wherein first fault positioning is carried out on a target area through the change conditions of state quantities of a circuit breaker and a relay before and after the ij fault of the transmission line, and the transmission line with the fault is found; and further on the premise of basing on kirchhoff's law of the fault line, the breadth-first search algorithm is improved, and the fault line is analyzed by using the improved breadth-first search algorithm through the current phasor and the voltage phasor before and after the fault of the power transmission line, so that more accurate fault positioning is realized.
2. The invention also uses the type recognition model trained in the source domain on the fault type recognition of the target domain through a transfer learning method, and obtains the three-phase current wavelet decomposition information entropy and the function threshold K of the three-phase short circuit through training the fault type recognition model3Information entropy and function threshold K of three-phase current wavelet decomposition with two-phase short circuit2Sum phase entropy difference threshold K2AB、K2BC、K2CACalculating three-phase current wavelet decomposition information entropy and function K and phase entropy difference K by using current phasor and voltage phasor before and after power transmission line fault of target regionAB、KBC、KCACompared with the prior art, the method can well judge whether the power transmission line with the fault has the short-circuit fault or not.
3. The invention also calculates A, B, C three-phase calculated current phasor through the voltage phasor before the fault line fault, calculates A, B, C three-phase actual current phasor through the current phasor after the fault line fault, and well judges whether the power transmission line with the fault has the line break fault by comparing A, B, C three-phase calculated current phasor with the actual current phasor.
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a schematic diagram of an IEEE39 bus system of the present invention;
FIG. 3 is a schematic diagram of the IEEE39 bus system fault location of the present invention;
fig. 4 is a diagram of a transmission line fault model according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments 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 inventive step, are intended to be within the scope of the present invention.
Example 1
As shown in fig. 1, the invention provides a method for locating and identifying a fault of a power transmission line, which comprises a fault locating method and a fault identifying method,
the fault positioning method comprises the following steps:
acquiring current phasor and voltage phasor before and after all transmission line ij faults in a target area and state quantities of circuit breakers and relays before and after the transmission line ij faults;
carrying out first fault positioning on the target area transmission line according to the state quantities of the circuit breaker and the relay before and after the ij fault of the transmission line;
carrying out second fault location on the power transmission line in the target area by adopting an improved breadth-first search algorithm through the current phasor, the voltage phasor and the first fault location before and after the ij fault of the power transmission line;
the improved breadth-first search algorithm comprises the steps that assuming that the original power flow direction of the power transmission line ij flows from a node i to a node j, the node i is defined as a first node, the node j is defined as an end point, and all power transmission lines located by the first fault are processed from the first node to the end point by adopting the breadth-first algorithm.
The fault type identification method comprises a short-circuit fault identification method and a broken line fault identification method,
the short-circuit fault identification method comprises the following steps:
acquiring current phasor, voltage phasor and fault types before and after a power transmission line fault occurs in a source domain;
taking current phasor and voltage phasor before and after the power transmission line with the source domain fault as input, taking the fault type as output, and training a fault type identification model;
three-phase current wavelet decomposition information entropy and function threshold K of three-phase short circuit are obtained by training fault type recognition model3Information entropy and function threshold K of three-phase current wavelet decomposition with two-phase short circuit2Sum phase entropy difference threshold K2AB、K2BC、K2CAIn which K is2＝K2AB+K2BC+K2CA；
Calculating three-phase current wavelet decomposition information entropy and function K and phase entropy difference K through current phasor and voltage phasor before and after the fault occurs in the power transmission line of the target areaAB、KBC、KCA；
Comparing the three-phase current wavelet decomposition information entropy with the function K and the phase entropy difference KAB、KBC、KCAThree-phase current wavelet decomposition information entropy and function threshold K of three-phase short circuit3Information entropy and function threshold K of three-phase current wavelet decomposition of two-phase short circuit2Sum phase entropy difference threshold K2AB、K2BC、K2CA；
When K is more than 0 and less than or equal to K3If so, judging the fault as a three-phase short circuit fault;
when K isAB＞K2ABIf so, judging the two-phase short-circuit fault of AB, and if K isBC＞K2BCIf yes, the two-phase short circuit fault is judged as BC two-phase short circuit fault, and when K is reachedCA＞K2CAIf so, judging the two-phase short circuit fault of the CA;
when K is3＜K≤K2And if so, judging the single-phase short-circuit fault.
Wherein the three-phase current wavelet decomposition information entropy and the function K are calculated according to the current phasor and the voltage phasor before and after the fault of the power transmission line with the fault in the target area, and comprise,
according to
Figure BDA0003562787940000051
Calculating wavelet information entropy W of A-phase currentAjWavelet information entropy W of B-phase currentBjWavelet information entropy W of sum C-phase currentCjWhere j is 1,2, …, m, m represents the dimension of high-dimensional wavelet decomposition, EjRepresents the entropy value of the j dimension of the high-dimensional wavelet decomposition,
Figure BDA0003562787940000052
represents the maximum value thereof;
calculating the difference value of AB phase entropy
Figure BDA0003562787940000053
Difference of BC phase entropy
Figure BDA0003562787940000054
And the difference of phase entropy of CA
Figure BDA0003562787940000055
Defining the information entropy sum function of three-phase current wavelet decomposition as K ═ KAB+KBC+KCA。
The method for identifying the disconnection fault comprises the following steps:
a, B, C three-phase calculated current phasor is calculated through the current phasor and the voltage phasor before the fault of the target domain power transmission line
Figure BDA0003562787940000056
Wherein,
Figure BDA0003562787940000057
representing A, B, C calculated current phasors for the three phases respectively,
Figure BDA0003562787940000058
respectively representing A, B, C three-phase voltage phasors before the fault of the first point of the power transmission line;
Figure BDA0003562787940000059
Figure BDA00035627879400000510
respectively representing A, B, C three-phase voltage phasors before the fault of the second point of the power transmission line;
Figure BDA00035627879400000511
an admittance matrix representing A, B, C three phases;
calculating A, B, C actual current phasor of three phases according to the current phasor and the voltage phasor of the power transmission line in the target domain after the fault
Figure BDA0003562787940000061
Wherein,
Figure BDA0003562787940000062
respectively A, B, C three-phase post-fault current phasors at the first point of the transmission line,
Figure BDA0003562787940000063
a, B, C three-phase current phasor after the fault of the second point of the power transmission line is respectively represented;
judgment of
Figure BDA0003562787940000064
Whether or not equal to
Figure BDA0003562787940000065
If so, the A phase has no disconnection fault, and if not, the A phase has the disconnection fault;
judgment of
Figure BDA0003562787940000066
Whether or not equal to
Figure BDA0003562787940000067
If so, the B phase has no disconnection fault, and if not, the B phase has a disconnection fault;
judgment of
Figure BDA0003562787940000068
Whether or not equal to
Figure BDA0003562787940000069
If so, the C phase has no disconnection fault, and if not, the C phase has the disconnection fault.
The transfer learning method is characterized in that the learning samples of the target domain are fewer, and more learning samples can be obtained in the source domain, so that the problem of fewer learning samples of the target domain is solved. However, the model for learning and training in the source domain is obtained under the sample thereof, and if the difference with the sample of the target domain is too large, the effect of applying the model in the source domain to the target domain will be reduced, so that the similarity test of the training samples of the source domain and the target domain needs to be performed, the training model of the sample data of the source domain with a larger degree of similarity is selected for migration, and the maximum mean difference of the sample of the source domain and the target domain is defined:
Figure BDA00035627879400000610
in the formula, XsA set of training samples representing a source domain; xtA set of samples representing a target domain; dH(Xs,Xt) A distance calculation result representing a Hilbert space H; the function phi represents mapping of high-dimensional samples to a low-dimensional space function; n is a radical of an alkyl radicalsRepresents the total number of source domain samples; n istRepresenting the total number of samples of the target domain.
This embodiment uses the IEEE39 bus system to verify the validity of the invention.
As shown in fig. 2, the bus system has 39 nodes, including 10 generator nodes (node 31 is a balance node), 29 load nodes, and 46 transmission lines, and the system parameters are shown in table 1.
TABLE 1
Figure BDA00035627879400000611
Figure BDA0003562787940000071
1. Fault location
Assuming that a transmission line short-circuit grounding fault occurs from the node 16 to the node 21, the fault is simulated, the simulation setting time is 800ms, the short-circuit fault occurs at the time of 200ms, and the fault time lasts about 12 cycles and is 189.7 ms.
Supposing that a PMU and a SCADA measuring device are installed on each node, the PMU can be used for observing the voltage phasor and the current phasor before and after the node palm bulging, and the SCADA can be used for obtaining four-remote quantity as the quantity measurement for fault positioning and fault type identification. And performing improved breadth-first search through the measured current phasor and voltage phasor to obtain the actual fault position of the power transmission line, as shown in fig. 3.
2. Fault type identification
In order to identify 16 types of faults (ABC three-phase short-circuit fault, AB phase short-circuit fault, BC phase short-circuit fault, CA phase short-circuit fault, AB phase short-circuit ground fault, BC phase short-circuit ground fault, CA phase short-circuit ground fault, a phase short-circuit fault, B phase short-circuit fault, C phase short-circuit fault, a phase open-circuit fault, B phase open-circuit fault, C phase open-circuit fault, AB phase open-circuit fault, BC phase open-circuit fault, CA phase open-circuit fault) in the target domain shown in fig. 3, it is necessary to perform identification model sample collection and training in the source domain.
As shown in fig. 4, the 220kV power transmission line model with the power transmission line simulation model having a length of 100km has two external power supplies respectively connected to two ends of BUS1 and BUS2, the frequency is set to 50Hz, the power transmission line parameter is set to have a resistance r of 0.02 Ω/km, a reactance x of 0.375 Ω/km, and a susceptance b of 0.458 × 10, excluding the conductance-5S/km。
Taking the fault sample as a source domain, sequentially selecting five points which are 0km, 25km, 50km, 80km and 100km away from the position of a bus1 on a power transmission line simulation model to carry out 16 types of fault models, and generating 2050 groups of fault sample data in total, wherein each type of fault sample data is shown in a table 2:
TABLE 2
Figure BDA0003562787940000072
Figure BDA0003562787940000081
And (3) performing convolutional neural network learning on 16 fault types in a source domain, and setting batch processing of the convolutional neural network as one fault type, wherein the batch processing is divided into 16 groups. The convolutional layers are set to 16 groups of 2-layer 3 × 3 stacked convolutional layers, each group of convolutional layers is connected with 1 layer of 2 × 2 pooling layers, the number of convolutional cores in each group is set to 128 (an Adam core optimizer is adopted, the speed attenuation factor is set to be 0.005, the learning rate is set to be 0.001, the training period is set to be 500), 4 layers of full-connected layers are set, and one output layer is arranged.
And (3) applying the fault type recognition model trained in the source domain to a target domain power transmission line, testing 16 fault types, and showing test results in table 3.
TABLE 3
Figure BDA0003562787940000082
Through comparison of a traditional BP neural network method and a Support Vector Machine (SVM) method, it can be found that the accuracy of the method in the embodiment can be kept above 97% and is about 4% higher than the accuracy of the other two methods when 16 types of faults are identified.
Example 2
Based on the same inventive concept of the above embodiment 1, the present invention further provides a system for analyzing and positioning a power transmission line fault, which comprises a fault positioning module, wherein the fault positioning module comprises,
the first obtaining module is used for obtaining current phasor and voltage phasor before and after the failure of all transmission lines ij in a target area, and state quantities of circuit breakers and relays before and after the failure of the transmission lines ij;
the first positioning module is used for carrying out first fault positioning on the target area transmission line ij through the state quantities of the circuit breaker and the relay before and after the transmission line ij fails, and determining the transmission line with the fault;
and the second positioning module is used for performing second fault positioning on the power transmission line with the fault by adopting an improved breadth-first search algorithm through the current phasor and the voltage phasor before and after the fault of the power transmission line ij, and determining the actual position of the fault.
Further, the present embodiment further includes a fault type identification module, where the fault type identification module includes,
the second obtaining module is used for obtaining current phasor, voltage phasor, state quantities of a circuit breaker and a relay and fault types before and after the fault of the source domain power transmission line;
the first training module is used for taking current phasor and voltage phasor before and after the source domain power transmission line fault and state quantities of a circuit breaker and a relay as input, taking the source domain power transmission line fault type as output and training a fault type identification model;
and the first processing module is used for applying the trained fault type identification model to a target domain by adopting a transfer learning method, and inputting current phasor and voltage phasor before and after the fault of the power transmission line of the target domain and state quantities of a circuit breaker and a relay to obtain the fault type of the power transmission line.
Example 3
Based on the same inventive concept as that of embodiment 1, the present invention further provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method for identifying and locating a power transmission line fault are implemented.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (8)

1. A method for positioning and identifying faults of a power transmission line is characterized by comprising the following steps:
acquiring current phasor and voltage phasor before and after all transmission line ij faults in a target area, and state quantities of circuit breakers and relays before and after the transmission line ij faults;
carrying out first fault location on the target area transmission line ij through the state quantities of the circuit breaker and the relay before and after the transmission line ij fails, and determining the transmission line with the fault;
carrying out second fault location on the power transmission line with the fault by adopting an improved breadth-first search algorithm according to the current phasor and the voltage phasor before and after the ij fault of the power transmission line, and determining the actual position of the fault;
the improved breadth-first search algorithm comprises the following steps that for any power transmission line with a fault, a breadth-first algorithm is adopted, and the processing from a first node to a terminal point is executed, wherein the first node and the terminal point are specifically as follows: when the original power flow flowing direction of the power transmission line ij flows from the node i to the node j, the node i is a first node, and the node j is a terminal point.
2. The method for positioning and identifying the transmission line fault according to claim 1, further comprising a fault type identification method, wherein the fault type identification method comprises a short-circuit fault identification method and a disconnection fault identification method, and the short-circuit fault identification method comprises the following steps:
acquiring current phasor, voltage phasor and fault types before and after a power transmission line fault occurs in a source domain;
taking current phasor and voltage phasor before and after the power transmission line with the source domain fault as input, taking the fault type as output, and training a fault type identification model;
and applying the trained fault type identification model to a target area by adopting a transfer learning method, and inputting current phasor and voltage phasor before and after the fault of the power transmission line with the fault in the target area to obtain the fault type of the power transmission line with the fault in the target area.
3. The method for positioning and identifying the transmission line fault according to claim 2, wherein the method for applying the transfer learning to apply the trained fault type identification model to the target domain comprises,
three-phase current wavelet decomposition information entropy and function threshold K of three-phase short circuit are obtained through training fault type recognition model3Information entropy and function threshold K of three-phase current wavelet decomposition with two-phase short circuit2Sum phase entropy difference threshold K2AB、K2BC、K2CAIn which K is2＝K2AB+K2BC+K2CA；
Calculating three-phase current wavelet decomposition information entropy and function K and phase entropy difference K through current phasor and voltage phasor before and after the fault occurs in the power transmission line of the target areaAB、KBC、KCA；
Comparing the three-phase current wavelet decomposition information entropy with the function K and the phase entropy difference KAB、KBC、KCAThree-phase current wavelet decomposition information entropy and function threshold K of three-phase short circuit3Information entropy and function threshold K of three-phase current wavelet decomposition of two-phase short circuit2Sum phase entropy difference threshold K2AB、K2BC、K2CA；
When K is more than 0 and less than or equal to K3If so, judging the fault as a three-phase short circuit fault;
when K isAB＞K2ABIf so, judging the two-phase short-circuit fault of AB, and if K isBC＞K2BCIf yes, the two-phase short circuit fault is judged as BC two-phase short circuit fault, and when K is reachedCA＞K2CAIf so, judging the two-phase short circuit fault of the CA;
when K is3＜K≤K2And if so, judging the single-phase short-circuit fault.
4. The method for positioning and identifying the transmission line fault according to claim 3, wherein the three-phase current wavelet decomposition information entropy and the function K are calculated according to the current phasor and the voltage phasor before and after the transmission line fault occurs in the target area, and the method comprises the steps of,
according to
Figure FDA0003562787930000021
Calculating wavelet information entropy W of A-phase currentAjWavelet information entropy W of B-phase currentBjWavelet information entropy W of C-phase currentCjWhere j is 1,2, …, m, m represents the dimension of high-dimensional wavelet decomposition, EjRepresents the entropy value of the j dimension of the high-dimensional wavelet decomposition,
Figure FDA0003562787930000022
represents the maximum value thereof;
calculating the difference value of AB phase entropy
Figure FDA0003562787930000023
Difference of BC phase entropy
Figure FDA0003562787930000024
And the difference of the phase entropy of CA
Figure FDA0003562787930000025
Defining the information entropy sum function of three-phase current wavelet decomposition as K ═ KAB+KBC+KCA。
5. The method for positioning and identifying the transmission line fault according to claim 2, wherein the method for identifying the disconnection fault comprises the following steps:
a, B, C three-phase calculated current phasor is calculated through the current phasor and the voltage phasor before the fault of the target domain power transmission line
Figure FDA0003562787930000026
Wherein,
Figure FDA0003562787930000027
representing A, B, C calculated current phasors for the three phases respectively,
Figure FDA0003562787930000031
respectively representing A, B, C three-phase voltage phasors before the fault of the first point of the power transmission line;
Figure FDA0003562787930000032
Figure FDA0003562787930000033
respectively representing A, B, C three-phase voltage phasors before the fault of the second point of the power transmission line;
Figure FDA0003562787930000034
an admittance matrix representing A, B, C three phases;
calculating A, B, C actual current phasor of three phases through the current phasor and the voltage phasor of the target domain power transmission line after fault
Figure FDA0003562787930000035
Wherein,
Figure FDA0003562787930000036
respectively A, B, C three-phase post-fault current phasors at the first point of the transmission line,
Figure FDA0003562787930000037
a, B, C three-phase current phasor after the fault of the second point of the power transmission line is respectively represented;
judgment of
Figure FDA0003562787930000038
Whether or not equal to
Figure FDA0003562787930000039
If so, the A phase has no disconnection fault, and if not, the A phase has the disconnection fault;
judgment of
Figure FDA00035627879300000310
Whether or not equal to
Figure FDA00035627879300000311
If so, the B phase has no disconnection fault, and if not, the B phase has a disconnection fault;
judgment of
Figure FDA00035627879300000312
Whether or not equal to
Figure FDA00035627879300000313
If so, the C phase has no disconnection fault, and if not, the C phase has the disconnection fault.
6. The system for analyzing and positioning the transmission line fault is characterized by comprising a fault positioning module, wherein the fault positioning module comprises a fault positioning module,
the first obtaining module is used for obtaining current phasor and voltage phasor before and after the faults of all the power transmission lines ij in a target area and state quantities of circuit breakers and relays before and after the faults of the power transmission lines ij;
the first positioning module is used for carrying out first fault positioning on the target area transmission line ij through the state quantities of the circuit breaker and the relay before and after the transmission line ij fails, and determining the transmission line with the fault;
and the second positioning module is used for carrying out second fault positioning on the power transmission line with the fault by adopting an improved breadth-first search algorithm through the current phasor and the voltage phasor before and after the fault of the power transmission line ij, and determining the actual position of the fault.
7. The system for analyzing and positioning the transmission line fault according to claim 6, further comprising a fault type identification module, wherein the fault type identification module comprises,
the second obtaining module is used for obtaining current phasor, voltage phasor, state quantities of a circuit breaker and a relay and fault types before and after the fault of the source domain power transmission line;
the first training module is used for taking current phasor and voltage phasor before and after the source domain power transmission line fault and state quantities of a circuit breaker and a relay as input, taking the source domain power transmission line fault type as output and training a fault type identification model;
and the first processing module is used for applying the trained fault type identification model to a target domain by adopting a transfer learning method, and inputting current phasor and voltage phasor before and after the fault of the power transmission line of the target domain and state quantities of a circuit breaker and a relay to obtain the fault type of the power transmission line.
8. A computer-readable storage medium characterized by: the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of a method for power transmission line fault localization identification as claimed in any one of claims 1 to 5.
CN202210294549.0A 2022-03-24 2022-03-24 Method and system for positioning and identifying transmission line fault Pending CN114594344A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117992644A (en) * 2024-04-07 2024-05-07 国网山东省电力公司沂水县供电公司 35KV and below electric power system fault location software system

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117992644A (en) * 2024-04-07 2024-05-07 国网山东省电力公司沂水县供电公司 35KV and below electric power system fault location software system

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