CN113156267B - Power distribution network ground fault section selection method and system - Google Patents
Power distribution network ground fault section selection method and system Download PDFInfo
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Abstract
The invention relates to a power distribution network ground fault section selection method and system. The method comprises the following steps: each detection node of the power distribution network acquires three-phase current waveforms of the section where the detection node is located, and acquires three-phase current variation waveforms; structure of the devicen（nAn integer greater than 1) can achieve in-situ identification of the feature quantity of the segment type and extract the corresponding feature quantitynA plurality of fault feature values; constructing a fault signature characterizing the segmentnDimensional data, i.e.A dimension feature vector; inputting the data of the section and the historical data into a clustering algorithm to identify whether the detection node is located upstream of a fault point; if the clustering result is that the circuit breaker is located at the upstream of the fault point, controlling the circuit breaker to wait for the action based on time delay of step-type matching, and realizing on-site selective fault isolation. The invention can realize the reliable in-situ positioning and isolation of the single-phase ground fault section.
Description
Technical Field
The invention relates to the technical field of fault positioning of power systems, in particular to a power distribution network ground fault section selection method and system.
Background
After the resonance grounding system generates single-phase grounding faults, in order to prevent the voltage rise and the insulation damage of non-fault phases, the single-phase grounding faults must be found out and isolated as soon as possible, otherwise, the single-phase grounding faults are easily expanded into two-point grounding faults or even multi-point grounding faults, the power failure range is enlarged, and certain harm is caused to the safety of electrical equipment and systems. Therefore, the problem of single-phase earth fault section selection of the power distribution network becomes a research hot spot.
The existing single-phase earth fault section selection method of the power distribution network mainly has the problems that communication is excessively dependent, threshold selection is difficult, a zero-sequence voltage-based method is not applicable, and the like, so that the section selection technology has poor application effect in an engineering field, and operation and maintenance staff can only use a manual line inspection mode to troubleshoot faults, and a large amount of manpower, material resources and financial resources are consumed.
Disclosure of Invention
The invention aims to provide a power distribution network ground fault section selection method and system, which can realize reliable on-site positioning and isolation of a single-phase ground fault section, do not need to train with a large amount of data, do not depend on communication and a master station, and do not depend on zero sequence voltage.
In order to achieve the above purpose, the technical scheme of the invention is as follows: a power distribution network ground fault segment selection method, comprising:
each detection node in a feeder line of the power distribution network acquires three-phase current waveforms of a section where the detection node is located, and acquires three-phase current variation waveforms;
analyzing the difference between the fault phase and non-fault phase current variation waveforms of each section, constructing n characteristic quantities capable of realizing the on-site identification of the section types so as to identify whether the detection node is positioned at the upstream of the fault point or not; wherein n is an integer greater than 1;
n feature quantities are fused, the cooperative judgment capability of different features is enhanced, the type of the section where the detection node is located is identified by using a clustering algorithm, and the section is judged to be an upstream section or other sections of the fault point, so that the on-site section selection is realized;
if the detection node is judged to be located in the upstream section of the fault point, the circuit breaker is controlled to wait for action based on time delay of step-type matching, and local selective fault isolation is achieved.
In an embodiment of the invention, the three-phase current waveform collects data of a previous power frequency cycle and N power frequency cycles after the fault, so as to obtain three-phase current variation waveforms of N power frequency cycles after the fault, and the data of M power frequency cycles from the moment of the fault can be taken for subsequent section selection research; wherein N is an integer greater than 0, and M is an integer or decimal less than or equal to N.
In one embodiment of the present invention, the n feature quantities that can realize in-situ identification of the segment types include correlation feature quantities, distance feature quantities, and unbalance feature quantities between waveforms.
In an embodiment of the invention, n feature quantities are fused, so that the feature quantities are complemented, the fault characteristics of each section are represented by n-dimensional data, and the fault tolerance of the section selection method under various special working conditions is enhanced.
In an embodiment of the present invention, the input of the clustering algorithm is n-dimensional feature quantity, and the output is 1-dimensional data, so as to identify whether the detection node is located in the upstream section of the fault point.
In an embodiment of the present invention, the implementation of on-site segment selection and selective fault isolation refers to a method that does not need to upload a large amount of complete wave recording data to a master station, and does not need to rely on the master station to implement segment positioning, so that the whole process of fault signal acquisition, fault feature extraction, segment type identification where the fault feature is located, and fault isolation can be implemented at each detection node.
In an embodiment of the present invention, the implementation of the in-situ selective fault isolation of the circuit breaker based on the time delay waiting action of the ladder type matching is specifically: the closer to the bus bar, the longer the set delay time, the shortest delay circuit breaker trips to isolate the fault section.
The invention also provides a power distribution network ground fault section selection system, which comprises feeder terminals and circuit breakers arranged on each section of the power distribution network, a memory, a processor and computer program instructions which are stored on the memory and can be operated by the processor;
the feeder line terminal at each detection node collects three-phase current waveforms of the section where the feeder line terminal is located and transmits the three-phase current waveforms to the processor;
the processor, when executing the computer program instructions, performs the steps of:
the feeder terminal calculates and processes the collected three-phase current data to obtain a three-phase current variation waveform;
extracting corresponding n fault characteristic quantities from the three-phase current variation waveform according to the constructed n characteristic quantities to obtain n-dimensional data representing the fault characteristic of the section;
inputting n-dimensional data into a clustering algorithm to judge whether a detection node corresponding to the feature is positioned at the upstream of a fault point;
if the circuit breaker is positioned at the upstream of the fault point, the circuit breaker is controlled to wait for action based on time delay of step-type matching, so that the local selective fault isolation is realized.
In an embodiment of the present invention, the n feature quantities of the structure are based on the difference between the fault phase current variation waveform and the non-fault phase current variation waveform of each section, and the n feature quantities are extracted, so as to obtain n-dimensional data representing the fault feature of the section.
In an embodiment of the present invention, the implementation of the in-situ selective fault isolation of the circuit breaker based on the time delay waiting action of the ladder type matching is specifically: the closer to the bus bar, the longer the set delay time, the shortest delay circuit breaker trips to isolate the fault section.
Compared with the prior art, the invention has the following beneficial effects:
1. in the invention, each distribution network feeder terminal only utilizes the three-phase current information monitored by itself, has self-possessed property, does not need to upload complete recording data to a main station, has small communication burden and does not depend on zero sequence voltage; the method can also realize the aims of rapid and on-site research, judgment and isolation of single-phase earth faults, is not dependent on the diagnosis of a main station, and improves the power supply reliability.
2. The multi-feature fusion method provided by the invention can enhance the collaborative decision capability of different features, improve the fault tolerance capability of the segment selection method under various special working conditions, is not influenced by factors such as network structure change, line type, transition resistance, compensation degree and the like, and simultaneously reduces the influence of factors such as noise interference, mutual inductor polarity reverse connection and the like on the segment selection method.
3. The method utilizes the clustering algorithm to identify the section types, has simple and reliable algorithm and high running speed, does not need training, reduces the influence of small sample problems, has strong adaptability to topological structures and system parameters, can adapt to complex working conditions of the field, and well solves the problem that the actual field fault data is difficult to acquire.
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FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a flow chart of a method according to an embodiment of the invention.
Fig. 3 is a schematic diagram of time delay protection of a circuit breaker based on ladder type matching.
Detailed Description
The technical scheme of the invention is specifically described below with reference to the accompanying drawings.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
As shown in fig. 1 and 2, the embodiment provides a method for selecting a section of a power distribution network ground fault, which specifically includes the following steps:
each detection node in a feeder line of the power distribution network acquires three-phase current waveforms of a section where the detection node is located, and acquires three-phase current variation waveforms;
analyzing the difference between the fault phase and non-fault phase current variation waveforms of each section, and constructing n (n is an integer greater than 1) characteristic quantities capable of realizing the on-site identification of the section types so as to identify whether the detection node is positioned at the upstream of a fault point or not;
n feature quantities are fused, the cooperative judgment capability of different features is enhanced, the type of the section where the detection node is located is identified by using a clustering algorithm, and the section is judged to be an upstream section or other sections of the fault point, so that the on-site section selection is realized;
if the detection node judges thatAnd the circuit breaker is controlled to wait for action based on time delay of step-type matching when the circuit breaker is positioned at the upstream of the fault point, so that the local selective fault isolation is realized. Taking the topology of the distribution network with only one feeder line in fig. 3 as an example, the feeder line is shown as having 6 sections, wherein the section 4 has a single-phase earth fault, and at this time, the detection nodes 1, 2, 3 and 4 are all judged to be located at the upstream of the fault point, and the time delay waiting actions of the corresponding circuit breakers based on step-type matching are controlled, specifically, the closer to the bus bar is the timing diagram, the longer the set delay time is, namely t 1 >t 2 >t 3 >t 4 >t 5 >t 6 At this point the circuit breaker 4 will wait t 4 After which the action is performed and the circuit breaker 3 will wait t 3 And then the action is executed, and the like, the circuit breaker 4 with the shortest delay is tripped firstly to isolate a fault section, the circuit is restored to normal operation, and the circuit breakers 1, 2 and 3 stop waiting actions to restore to a original state.
Preferably, the fault data in the embodiment are derived from a 10kV power distribution network simulation model built on PSCAD/EMTDC software, and the collected simulation data are three-phase current waveforms of a power frequency period before the fault occurs and a power frequency period after the fault occurs; the method comprises the steps of constructing four characteristic quantities of gray correlation degree, euclidean distance, bantaqili coefficient and offset coefficient; the clustering algorithm adopts k-means clustering.
In this embodiment, the three-phase current variation waveform is obtained specifically as follows:
Δi＝i(t 0 +T)-i(t 0 -T)；
wherein delta i is expressed as the phase current variation of the first power frequency cycle after the fault, i is the original phase current, t 0 And the fault time is the power frequency period. The equation indicates that the phase current variation in the first power frequency period after the fault can be obtained by subtracting the phase current in the previous cycle after the fault from the phase current in the previous cycle after the fault.
The sampling frequency of the simulation model of the embodiment is 10kHz, the sampling point number of the three-phase current waveform is 400, so that 3×400 waveform data are collected at each detection node. The number of sampling points of the three-phase current variation waveform is 200.
In this embodiment, the gray correlation feature extraction is specifically as follows:
wherein r is XY For gray correlation between two-phase current variation waveforms, three correlation coefficients can be obtained at each detection node, which is r AB 、r AC And r BC The correlation coefficient of the phase current variation waveforms of the AB two phases, the AC two phases and the BC two phases in the first power frequency period after the fault is respectively set; x (n) and Y (n) are two different phase current variation waveforms, i A (n)、i B (n) and i C (n); n is the sampling point number of the waveform and is 200; n is the data of the nth sampling point in the waveform; ζ is the gray resolution factor, the interval between values is (0, 1), here 0.5.
The gray correlation degree is to judge whether the relationship is tight according to the similarity degree between curves, r XY The larger the two curves are, the more similar the two curves are, where for the section upstream of the fault point, the degree of correlation between the fault phase and the non-fault phase is smaller, and the degree of correlation between the non-fault phase is larger, approaching 1; for the downstream section of the fault point and the sound line section, the association degree of the fault phase and the non-fault phase is larger. Therefore, the minimum value of the three is selected as the fault characteristic quantity.
In this embodiment, the euclidean distance feature extraction process is specifically as follows:
firstly, the three-phase current variation waveform is normalized, and the formula is as follows
Wherein i is A (n)、i B (n) and i C (n) is a three-phase current variation waveform; i.e A ′(n)、i B ' (n) and i C 'n' is normalized three-phaseA current variation waveform; n is the sampling point number of the waveform and is 200; n represents the nth sample point in the waveform.
And then calculating the distance between the two curves by using the Euclidean distance formula, wherein the formula is as follows
Wherein d XY For Euclidean distance between two-phase current variation waveforms, three Euclidean distances can be obtained at each detection node, and d is AB 、d AC And d BC The Euclidean distance of the first power frequency period after the fault of the phase current variation waveforms of the AB two phases, the AC two phases and the BC two phases is respectively; the normalized phase current variation waveforms of which X (n) and Y (n) are two different phases can be i A ′(n)、i B ' (n) and i C ′(n)。
d XY The smaller the curve is, the more similar the curves are, the larger the curve is, where d is chosen AB 、d AC And d BC The maximum value of (a) is used as the fault characteristic quantity.
In this embodiment, the extraction process of the patadine coefficient feature quantity is specifically as follows:
firstly, the three-phase current variation waveform needs to be normalized, and the formula is as follows
Wherein i is A (n)、i B (n) and i C (n) is a three-phase current variation waveform; i.e A ′(n)、i B ' (n) and i C ' n is the normalized three-phase current variation waveform; n is the sampling point number of the waveform and is 200; n represents the nth sample point in the waveform.
Then, the overlapping amount of the two curves is calculated by using the Bantaqili coefficient, and the formula is as follows
Wherein B is XY For the Banta QIAGEN coefficients between the two-phase current variation waveforms, three Banta QIAGEN coefficients can be obtained at each detection node, which is B AB 、B AC And B BC The phase current variation waveforms of the AB two phases, the AC two phases and the BC two phases are respectively the Bantaqian coefficients of the first power frequency period after the fault; k is the number of blocks; x is X k And Y k The ratio of the sampling points of the normalized X-phase current variation waveform and the normalized Y-phase current variation waveform distributed in the kth equal division block to the sampling points of one power frequency period is 200.
The number of tiles K is too small, resulting in overestimation of the overlapping area and loss of accuracy, but if K is too large, it can result in too many empty tiles and loss of accuracy. The larger the pataliya coefficient (closer to 1) the higher the overlap ratio of the two curves, the pataliya coefficient is equal to 0 when the two curves are not overlapped at all. Thus, choose B AB 、B AC And B BC As a fault characteristic quantity.
In this embodiment, the offset coefficient feature quantity extraction is specifically as follows:
wherein k is a three-phase current variation offset coefficient, each detection node can obtain an offset coefficient, and the larger the offset coefficient is, the more dissimilar the three-phase current variation waveforms of the section are, namely the higher the possibility that the section is a fault section is; x (n) is a phase current variation waveform, and may be i A (n)、i B (n) and i C (n) obtaining K correspondingly A 、K B 、K C Three current values; n isThe number of sampling points of the waveform is 200; n is the data of the nth sampling point in the waveform.
In this embodiment, the clustering algorithm adopts k-means clustering, and the specific implementation process is as follows:
1) The input data set is input into 1X 4 dimension data, namely, the input data of the clustering algorithm at each detection node is four characteristic values;
2) Initializing parameters: setting the clustering number as 2, namely distinguishing whether the detection node is positioned at the upstream of the fault point or not, so that two groups are hoped to be obtained through clustering;
3) Randomly allocating the positions of the center points of the 2 categories;
4) By calculating the distance from each input data point to each class center point, and assigning it to the set where the nearest class center point is located, the distance calculation uses the Euclidean distance as follows:
wherein X is i For the ith input data, C j X is the center of the j th class it T-th data representing i-th input data, C jt The t-th dimension data representing the j-th category center, m being the dimension of the cluster data, here 3;
5) Calculating the center points of the two class clusters again, taking the average value of the sets of the two class clusters, and then turning to the 4 th step until convergence;
6) And obtaining a type identification result of the section where the detection node is located.
In this embodiment, the implementation of the on-site selective fault isolation of the circuit breaker based on the time delay waiting action of the ladder-type coordination is specifically: the closer to the bus bar, the longer the set delay time, the shortest delay circuit breaker trips to isolate the fault section.
The embodiment also provides a power distribution network ground fault section selection positioning system, which comprises feeder terminals and circuit breakers arranged on each section of the power distribution network, a memory, a processor and computer program instructions which are stored on the memory and can be run by the processor;
the feeder line terminal at each detection node collects three-phase current waveforms of the section where the feeder line terminal is located and transmits the three-phase current waveforms to the processor;
the processor, when executing the computer program instructions, performs the steps of:
the feeder terminal calculates and processes the acquired data to acquire a three-phase current variation waveform of a first power frequency period after a fault;
according to the constructed fusion multi-feature quantity principle, four fault feature quantities of gray correlation degree, euclidean distance, bantaqili coefficient and offset coefficient are extracted to obtain 4-dimensional data representing fault features of the section;
inputting the 4-dimensional data into a k-means clustering algorithm to judge whether the detection node is positioned at the upstream of the fault point;
if the circuit breaker is positioned at the upstream of the fault point, the circuit breaker is controlled to wait for action based on time delay of step-type matching, so that the local selective fault isolation is realized.
In this embodiment, a 10kV radiation type resonant grounding system simulation model is built by using PSCAD/EMTDC simulation software, and includes 5 feeder lines, and three feeder lines include branch lines, various single-phase grounding faults are simulated in the simulation model, each detection node obtains three-phase current waveforms of one period before and after the fault of the section, so as to obtain three-phase current variation waveforms of the first power frequency period after the fault, and after four feature quantities of gray association degree, euclidean distance, barta qili coefficient and offset coefficient are extracted, a 1×4 dimension feature vector representing the fault feature of the section is constructed, the feature vector is input into a k-means clustering algorithm together with historical data, a clustering result of the section is obtained, so as to identify the section type, and finally a feeder line terminal located at the detection node upstream of the fault point will control a circuit breaker at the position to be based on a time delay waiting action of step-type matching, and the circuit breaker with the shortest delay is tripped, so that the single-phase fault section is reliably positioned in place.
The samples selected in the embodiment are derived from 40 times of single-phase earth fault simulation data of the power distribution network, and comprise 360 groups of sample data, wherein 180 groups of samples are selected as historical data, and the rest 180 groups of sample data are tested.
The single-phase earth fault section selection method of the power distribution network comprises the following steps:
(1) Acquisition of three-phase current variation waveform
After three-phase current data of each section are collected, three-phase current waveforms of a previous power frequency period and a next power frequency period of a single-phase grounding fault are obtained, namely, three-phase current waveforms containing two power frequency periods are obtained, and the sampling point number is 400. And then acquiring the current variation waveforms of each phase in the first power frequency period after the fault, wherein the sampling point number is 200. Three one-dimensional sequences representing the length of the line section of 200, namely A, B, C three-phase current variation waveforms of the first power frequency period after the fault, can be obtained at each detection node.
(2) Extraction of multiple feature quantities
In this embodiment, four fault feature values are extracted, which are gray correlation, euclidean distance, pataliya coefficient, and offset coefficient. Through the formula, three gray correlation coefficients, three Euclidean distance coefficients, three Banta QIAGEN coefficients and one offset coefficient can be obtained for each section, the gray correlation and the Banta QIAGEN coefficients all take the minimum value in each, the Euclidean distance takes the maximum value, and finally 1X 4-dimensional data representing the fault characteristics of each section can be obtained at each detection node.
(3) Cluster identification segment type
The present embodiment utilizes a k-means clustering algorithm to identify the segment type to determine whether the detection node here is located upstream of the failure point. A vector of 1×4 dimensions is input, a type discrimination vector of 1×1 is returned, the correspondence is 1 indicating that the section is located upstream of the fault point, and 2 indicating that the section is located in the other section.
(5) In-situ selective isolation of single-phase earth fault sections
If the feeder terminal at the detection node is located in the upstream section of the fault point, the circuit breaker is controlled to wait for action based on the step-type time delay, and if the delay in the waiting action is the shortest, the tripping action (namely, the fault is located in the section) is executed. Otherwise, the other shortest delay circuit breaker will trip, the fault is isolated, the network returns to normal, and the circuit breaker stops waiting (i.e. the fault is located in the downstream section). In the embodiment, the accuracy of the ground fault section selection is 100%.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the invention in any way, and any person skilled in the art may make modifications or alterations to the disclosed technical content to the equivalent embodiments. However, any simple modification, equivalent variation and variation of the above embodiments according to the technical substance of the present invention still fall within the protection scope of the technical solution of the present invention.
Claims (9)
1. A method for selecting a section of a power distribution network ground fault, comprising the steps of:
each detection node in a feeder line of the power distribution network acquires three-phase current waveforms of a section where the detection node is located, and acquires three-phase current variation waveforms;
analyzing the difference between the fault phase and non-fault phase current variation waveforms of each section, and constructing m characteristic quantities capable of realizing the on-site identification of the section types so as to identify whether the detection node is positioned at the upstream of the fault point or not; wherein m is an integer greater than 1;
the construction m feature quantities capable of realizing the on-site identification of the section type, including correlation feature quantities, distance feature quantities and unbalance feature quantities among waveforms; in particular, the method comprises the steps of,
the correlation characteristic quantity among waveforms is gray correlation characteristic quantity, and the extraction mode is as follows:
wherein r is XY For gray correlation between two-phase current variation waveforms, three correlation coefficients can be obtained at each detection node, which is r AB 、r AC And r BC Phase current variation waveforms of AB two phase, AC two phase and BC two phase respectivelyThe correlation coefficient of the first power frequency period after the fault; x (n) and Y (n) are two different phase current variation waveforms of i A (n)、i B (n) or i C (n); n is the number of sampling points of the waveform; n is the data of the nth sampling point in the waveform; ζ is the gray resolution factor;
the distance characteristic quantity is Euclidean distance characteristic quantity, and the extraction mode is as follows:
firstly, the three-phase current variation waveform is normalized, and the formula is as follows
Wherein i is A (n)、i B (n) and i C (n) is a three-phase current variation waveform; i.e A ′(n)、i B ' (n) and i C ' n is the normalized three-phase current variation waveform;
and then calculating the distance between the two curves by using the Euclidean distance formula, wherein the formula is as follows
Wherein d XY For Euclidean distance between two-phase current variation waveforms, three Euclidean distances can be obtained at each detection node, and d is AB 、d AC And d BC The Euclidean distance of the first power frequency period after the fault of the phase current variation waveforms of the AB two phases, the AC two phases and the BC two phases is respectively; x '(n) and Y' (n) are normalized phase current variation waveforms of two different phases, i A ′(n)、i B ' (n) or i C ′(n)；
The imbalance characteristic quantity is a pataliya coefficient characteristic quantity and an offset coefficient characteristic quantity, wherein the extraction mode of the pataliya coefficient characteristic quantity is as follows:
the overlapping amount of the two curves is calculated by using the Bantaqili coefficient, and the formula is as follows
Wherein B is XY For the Bantaqian coefficients between the two-phase current variation waveforms, three Bantaqian coefficients can be obtained at each detection node, which is B AB 、B AC And B BC The phase current variation waveforms of the AB two phases, the AC two phases and the BC two phases are respectively the Bantaqian coefficients of the first power frequency period after the fault; k is the number of blocks; x is X k And Y k The ratio of the sampling points of the normalized X-phase current variation waveform and the normalized Y-phase current variation waveform distributed in the kth equal division block to the sampling points of one power frequency period is respectively;
the extraction mode of the offset coefficient characteristic quantity is as follows:
wherein k is a three-phase current variation offset coefficient, each detection node can obtain an offset coefficient, and the larger the offset coefficient is, the more dissimilar the three-phase current variation waveforms of the section are, namely the higher the possibility that the section is a fault section is; x (n) is a phase current variation waveform, i A (n)、i B (n) or i C (n) obtaining K correspondingly A 、K B 、K C Three current values;
the m feature quantities are fused, the cooperative judgment capability of different features is enhanced, the type of the section where the detection node is located is identified by using a clustering algorithm, and the section is judged to be an upstream section or other sections of the fault point, so that the on-site section selection is realized;
if the detection node is judged to be located in the upstream section of the fault point, the circuit breaker is controlled to wait for action based on time delay of step-type matching, and local selective fault isolation is achieved.
2. The method for selecting the section of the power distribution network grounding fault according to claim 1, wherein the three-phase current waveform is acquired by data of a power frequency cycle before the fault and K power frequency cycles after the fault, so that three-phase current variation waveforms of K power frequency cycles after the fault are obtained, and the data of M power frequency cycles from the moment of the fault can be taken for subsequent section selection research; wherein K is an integer greater than 0, and M is an integer or decimal less than or equal to K.
3. The method for selecting the section of the power distribution network ground fault according to claim 1, wherein m characteristic quantities are fused, so that the characteristic quantities are complemented, the fault characteristics of each section are represented by m dimensions, and the fault tolerance of the section selecting method under various special working conditions is enhanced.
4. The method for selecting the section of the power distribution network ground fault according to claim 1, wherein the input of the clustering algorithm is m-dimensional characteristic quantity, and the output is 1-dimensional data so as to identify whether the detection node is located in the section upstream of the fault point.
5. The method for selecting the section of the power distribution network ground fault according to claim 1, wherein the method for realizing the on-site section selection and the selective fault isolation is a method for realizing the whole process of fault signal acquisition, fault feature extraction, section type identification where the fault is located and fault isolation at each detection node without uploading a large amount of complete wave recording data to a main station and without relying on the main station to realize section positioning.
6. The method for selecting the section of the power distribution network ground fault according to claim 1, wherein the circuit breaker is based on a time delay waiting action of step-type matching, and the implementation of the in-situ selective isolation fault is specifically as follows: the closer to the bus bar, the longer the set delay time, the shortest delay circuit breaker trips to isolate the fault section.
7. The power distribution network ground fault section selection system is characterized by comprising feeder terminals and circuit breakers which are arranged on each section of the power distribution network, a memory, a processor and computer program instructions which are stored on the memory and can be run by the processor;
the feeder line terminal at each detection node collects three-phase current waveforms of the section where the feeder line terminal is located and transmits the three-phase current waveforms to the processor;
the processor, when executing the computer program instructions, performs the steps of:
the feeder terminal calculates and processes the collected three-phase current data to obtain a three-phase current variation waveform;
constructing m feature quantities capable of realizing in-situ identification of the section type so as to identify whether the detection node is positioned upstream of the fault point or not; wherein m is an integer greater than 1; the construction m feature quantities capable of realizing the on-site identification of the section type, including correlation feature quantities, distance feature quantities and unbalance feature quantities among waveforms; in particular, the method comprises the steps of,
the correlation characteristic quantity among waveforms is gray correlation characteristic quantity, and the extraction mode is as follows:
wherein r is XY For gray correlation between two-phase current variation waveforms, three correlation coefficients can be obtained at each detection node, which is r AB 、r AC And r BC The correlation coefficient of the phase current variation waveforms of the AB two phases, the AC two phases and the BC two phases in the first power frequency period after the fault is respectively set; x (n) and Y (n) are two different phase current variation waveforms of i A (n)、i B (n) or i C (n); n is the number of sampling points of the waveform; n is the data of the nth sampling point in the waveform; ζ is the gray resolution factor;
the distance characteristic quantity is Euclidean distance characteristic quantity, and the extraction mode is as follows:
firstly, the three-phase current variation waveform is normalized, and the formula is as follows
Wherein i is A (n)、i B (n) and i C (n) is a three-phase current variation waveform; i.e A ′(n)、i B ' (n) and i C ' n is the normalized three-phase current variation waveform;
and then calculating the distance between the two curves by using the Euclidean distance formula, wherein the formula is as follows
Wherein d XY For Euclidean distance between two-phase current variation waveforms, three Euclidean distances can be obtained at each detection node, and d is AB 、d AC And d BC The Euclidean distance of the first power frequency period after the fault of the phase current variation waveforms of the AB two phases, the AC two phases and the BC two phases is respectively; x '(n) and Y' (n) are normalized phase current variation waveforms of two different phases, i A ′(n)、i B ' (n) or i C ′(n)；
The imbalance characteristic quantity is a pataliya coefficient characteristic quantity and an offset coefficient characteristic quantity, wherein the extraction mode of the pataliya coefficient characteristic quantity is as follows:
the overlapping amount of the two curves is calculated by using the Bantaqili coefficient, and the formula is as follows
Wherein B is XY For the Bantaqian coefficients between the two-phase current variation waveforms, three Bantaqian coefficients can be obtained at each detection node, which is B AB 、B AC And B BC The phase current variation waveforms of the AB two phases, the AC two phases and the BC two phases are respectively the Bantaqian coefficients of the first power frequency period after the fault; k is a blockA number; x is X k And Y k The ratio of the sampling points of the normalized X-phase current variation waveform and the normalized Y-phase current variation waveform distributed in the kth equal division block to the sampling points of one power frequency period is respectively;
the extraction mode of the offset coefficient characteristic quantity is as follows:
wherein k is a three-phase current variation offset coefficient, each detection node can obtain an offset coefficient, and the larger the offset coefficient is, the more dissimilar the three-phase current variation waveforms of the section are, namely the higher the possibility that the section is a fault section is; x (n) is a phase current variation waveform, i A (n)、i B (n) or i C (n) obtaining K correspondingly A 、K B 、K C Three current values;
extracting corresponding m fault characteristic quantities from the three-phase current variation waveform according to the constructed m characteristic quantities to obtain m-dimensional data representing fault characteristics of the section;
inputting m-dimension data into a clustering algorithm to judge whether a detection node corresponding to the feature is positioned at the upstream of a fault point;
if the circuit breaker is positioned at the upstream of the fault point, the circuit breaker is controlled to wait for action based on time delay of step-type matching, so that the local selective fault isolation is realized.
8. The system according to claim 7, wherein the m feature quantities are based on the difference between the fault phase current variation waveform and the non-fault phase current variation waveform of each section, and the m feature quantities are extracted to obtain m-dimensional data representing the fault feature of the section.
9. The power distribution network ground fault section selection system according to claim 7, wherein the circuit breaker is based on a time delay waiting action of step-type matching, and the implementation of the in-situ selective isolation fault is specifically as follows: the closer to the bus bar, the longer the set delay time, the shortest delay circuit breaker trips to isolate the fault section.
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