CN109541395B - Distribution network section positioning method based on Hausdorff under characteristic frequency band - Google Patents

Distribution network section positioning method based on Hausdorff under characteristic frequency band Download PDF

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CN109541395B
CN109541395B CN201811409931.1A CN201811409931A CN109541395B CN 109541395 B CN109541395 B CN 109541395B CN 201811409931 A CN201811409931 A CN 201811409931A CN 109541395 B CN109541395 B CN 109541395B
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李振兴
王朋飞
傅裕挺
李振华
徐艳春
邱立
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China Three Gorges University CTGU
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    • 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
    • G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors

Abstract

A distribution network section positioning method based on Hausdorff under a characteristic frequency band is characterized in that by analyzing the fault characteristics of transient zero-sequence current free component, the information amplitude ratio characteristics of an upstream adjacent node of a fault point and the characteristic frequency band of the upstream adjacent node and a downstream node are determined, the same frequency band of the transient zero-sequence current free component of the upstream adjacent node of the fault point is obtained, the characteristic frequency band is selected by taking the characteristic frequency band of a previous-stage node in the adjacent nodes as a reference, the amplitude ratio k >1 is obtained, the characteristic frequency bands of the transient zero-sequence current free component of the upstream adjacent node of the fault point are the same, and the information matching. And normalizing the frequency band information to conveniently construct a reliable criterion. And further, introducing an image matching algorithm Hausdorff to measure and calculate the transient current characteristics of the adjacent nodes. In order to eliminate data asynchronism, a data window translation optimization strategy is provided, a matching degree value is finally obtained, a threshold value is further set, and a fault section is compared and judged.

Description

Distribution network section positioning method based on Hausdorff under characteristic frequency band
Technical Field
The invention relates to a distribution network feeder section positioning method aiming at a distribution network, in particular to a distribution network section positioning method based on Hausdorff under characteristic frequency band
Background
The national energy agency publishes action plan for power distribution network construction in 2015, and points out that the investment for power distribution network modification is not less than 2 trillion, the target requirement is that the intelligent level of power distribution is improved, the power supply reliability reaches 99.99%, the annual average power failure time of users does not exceed 1 hour, and the international advanced level is reached. At present, the domestic power distribution network connection mode basically adopts the mode that a neutral point is not grounded or is grounded through an arc suppression coil. When a single-phase earth fault occurs on a distribution feeder of an arc suppression coil grounding system, zero-sequence current power frequency information of a fault circuit is converged with a non-fault circuit, and a conventional fault positioning method is difficult to apply. Considering that the occurrence frequency of the single-phase earth fault is high, generally about 80%, when the system fails, a fault point is quickly searched, and the fault isolation is very necessary.
In order to solve the problems and achieve the aims, some innovative achievements appear in practical engineering, and researches and applications such as a signal injection method (direct current, alternating current and alternating current/direct current signals), a linear correlation method, a deep learning algorithm and the like are gradually put into the positioning of the sections of the power distribution network. For the linear correlation method, the method is still influenced by a system grounding mode and a positioning blind area.
Disclosure of Invention
In order to solve the technical problem, the invention provides a distribution network section positioning method based on Hausdorff under a characteristic frequency band, which determines the characteristic of the information amplitude ratio of the characteristic frequency bands of an upstream adjacent node and a downstream node of a fault point by analyzing the fault characteristic of the transient zero-sequence current free component, and obtains the amplitude ratio k >1 of the same frequency band of the transient zero-sequence current free component of the upstream adjacent node of the fault point (the characteristic frequency band is selected by taking the characteristic frequency band of the upper-level node in the adjacent node as the reference), while the characteristic frequency band of the transient zero-sequence current free component of the upstream adjacent node of the fault point is the same and the information matching degree is high. And normalizing the frequency band information to conveniently construct a reliable criterion. And further, introducing an image matching algorithm Hausdorff to measure and calculate the transient current characteristics of the adjacent nodes. In order to eliminate data asynchronism, a data window translation optimization strategy is provided, a matching degree value is finally obtained, a threshold value is further set, and a fault section is compared and judged. The method eliminates the influence of a system grounding mode and a positioning blind area on the positioning accuracy.
The technical scheme adopted by the invention is as follows:
a distribution network section positioning method based on Hausdorff under a characteristic frequency band comprises the steps of firstly, adaptively selecting a single-node characteristic frequency band according to a wavelet packet based on an energy maximization principle, then, carrying out normalization processing on information of the same frequency band as a next-stage node by taking the single-node characteristic frequency band as a reference, translating by relying on a data window, inputting the translated data information into a husdorff distance algorithm, traversing to obtain a minimum distance value H, obtaining a distance value reflecting the integral amplitude difference of adjacent nodes, and determining a matching degree HS; further, by comparing with the set threshold value, the fault section can be effectively distinguished.
The processing flow of the method comprises characteristic frequency band selection, frequency band information normalization, matching degree optimization scheme and threshold setting.
The method introduces an image matching algorithm Hausdorff for positioning the feeder section of the power distribution network, and the characteristic capturing and characteristic matching capabilities are strong.
A distribution network section positioning method based on Hausdorff under characteristic frequency bands comprises the following steps:
step 1: transient current data meeting the requirements of wavelet packet decomposition and a Huasdorff distance algorithm are obtained according to power distribution reality, and first, transient zero-sequence current data of 1 cycle wave at an x node and a next x +1 node of a feeder line bus end are obtained.
Step 2: selecting wavelet base dbn and decomposing the wavelet base dbn into s layers, and decomposing the data of the two nodes into frequency band information by utilizing a wavelet packet decomposition tool.
And step 3: bonding the s-th layer 2s-1 frequency band information (non-fundamental wave), selecting a characteristic frequency band of an x node of a bus terminal based on a wavelet packet energy maximum principle, extracting transient free component information of the characteristic frequency band and current information of the same frequency band of a next level of x +1 node, namely the same frequency band of two nodes, and performing normalization processing.
And 4, step 4: based on the acquired normalized frequency band information, matching degree optimization processing is carried out on adjacent nodes by using a Huasdorff distance algorithm, and the matching degree HS is obtainedx→x+1。
And 5: comparison HSx→x+1Sum criterion threshold HSsetIf HSx→x+1<HSsetThen the sector is a faulty sector. If HSx→x+1>HSsetThe sector is a normal sector. And further determining the next section x +1 → x +2, and circulating the steps 1 to 5 until the node of the end of the feeder line.
In the step 2, in order to eliminate the influence of different neutral point grounding modes on the fault positioning accuracy, a wavelet packet is used for carrying out frequency band decomposition, and the transient zero-sequence current obtained in the step 1 is decomposed into frequency band information of different frequency bands. Wherein the wavelet basis is selected from dbN and the number of decomposition layers s. Considering the problems of smooth result, fast decomposition, concentrated signal energy and the like, N is 10, and s is 4.
In the step 3, the band energy is utilized mostGeneral principle to choose 2sThe selection principle depends on that the characteristic frequency band information contains fault transient zero sequence current main frequency information, the amplitude of the main frequency information is maximum, and the energy value is maximum, wherein the characteristic frequency band information (non-fundamental wave) is a characteristic frequency band in 1 frequency band information (formula (1)). And normalizing the characteristic frequency band of the x node and the information of the same frequency band of the x +1 node.
Figure BDA0001878249920000021
In the formula (1), j is 1,2,3, L, s, k is 1,2,3, L,2s(ii) a i is 1,2,3, L, N; the sampling point number is 0.5 cycle, and the complete transient information after the fault is contained; s is the maximum number of layers of wavelet decomposition;
Figure BDA0001878249920000031
and
Figure BDA0001878249920000032
zero sequence current and energy of the xth section switch of the kth frequency band of the s layer are obtained, and the maximum value of x is K;
Figure BDA0001878249920000033
(equivalent to
Figure BDA0001878249920000034
) Is 1,2L 2 of the s-th layers-1,2sAn energy value of the frequency band; k is a radical ofmaxIs s layer 2sAnd 1 frequency band serial number with the maximum energy in the transient zero-sequence current free component frequency band.
In the step 4, the error of 1-3 ms existing in the existing time synchronization mode of the intelligent acquisition terminal is considered, the accuracy of the criterion is affected, and the actual characteristics of the data cannot be reflected. Based on the problem, the matching degree optimization scheme adopts a data window translation method to eliminate the problem.
Let the step length of single movement of data window be 1/fsThe width of the moving data is +/-3 ms, and the maximum value of the total moving step number is N' ═ 3 × 10-3×fsThe feeder line section corresponding to the section switch serial number x is x→ X +1, the number of feeder line section switches is X, the matching degree HSx→x+1Comprises the following steps:
Figure BDA0001878249920000035
in the formula (2), N is 0.5 cycle sampling points (including complete transient information after a fault) in the data window; n' is a movable step length;
Figure BDA0001878249920000036
node x and x +1 transient zero sequence current frequency band information normalization sequences are respectively.
In the data window length determination, in order to satisfy the matching degree optimization scheme, that is, after the data window is ensured to move, the input data of the Haudorff distance algorithm can keep the same number of points N, so that a margin 2 x N' needs to be left in the data window. Maximum error 3ms, f considering time synchronization modesIt is calculated that the margin is determined as 100 sampling points at 10kHz, and the length of the data window is determined as 1 cycle, i.e., 50 sampling points are respectively extended to the left and right on the basis of the N sampling point data. The determination of the data window may be adjusted depending on engineering practices.
In the step 4, a threshold setting method and an action criterion are constructed:
to ensure the reliability of the sector positioning, the ideal matching degree value HS is usedTReliability factor KrelA criterion threshold HS is setset. The threshold value is:
HSset＝HST/Krel
in the formula KrelGenerally, the amount is 1.15-1.3. Due to HSTNot to take K when being equal to 1rel＝1.2(KrelCan be set according to actual engineering), and then the HS is obtained by combining the formulaset＝0.83。
If HSx→x+1<HSsetThe faulty section is x → x +1, otherwise, it is the normal section.
The distribution network section positioning method based on Hausdorff under the characteristic frequency band has the following beneficial effects:
(1) the intelligent power distribution network system is suitable for emerging intelligent power distribution network systems and has an engineering platform, such as a highly intelligent urban power distribution network system built in 2018 by Beijing.
(2) The method is not influenced by the change of the grounding mode of the neutral point of the system and the data asynchronism.
(3) The method avoids the positioning blind zone of a linear correlation method (correlation coefficient method).
(4) In order to form a criterion and set a threshold value conveniently, the same frequency bands of adjacent nodes are subjected to normalization processing, and a more reliable and accurate section positioning method is obtained by introducing a Hausdorff distance algorithm and combining a matching degree optimization scheme and threshold value setting.
Drawings
Fig. 1(a) is a model diagram of a power distribution network grounded through arc suppression coils.
Fig. 1(b) is a model diagram of a distribution network with a neutral point not grounded.
Fig. 2 is a flow chart of single-node characteristic frequency band adaptive selection.
Fig. 3(a) is an A, B node characteristic frequency band information diagram.
Fig. 3(b) is a graph of the normalization processing result of the graph (a).
FIG. 4 is a flow chart of a segment locating method.
Detailed Description
A distribution network section positioning method based on Hausdorff under a characteristic frequency band determines an upstream adjacent node of a fault point and characteristic frequency band information amplitude ratio characteristics of the upstream adjacent node and a downstream node of the fault point by analyzing transient zero sequence current free component fault characteristics, obtains the same frequency band of the transient zero sequence current free component of the adjacent node at the fault point, selects the characteristic frequency band by taking a previous-stage node characteristic frequency band in the adjacent node as a reference, and has the amplitude ratio k > 1. And (3) introducing a Hausdorff distance algorithm with image feature matching and strong abnormal data tolerance, measuring and calculating the transient zero-sequence current amplitude feature matching degree based on the upstream feature frequency band as a reference, and further effectively distinguishing the fault section by comparing with a set threshold.
The section positioning method comprises the steps of characteristic frequency band selection, frequency band information normalization, a matching degree optimization scheme and threshold setting.
A distribution network section positioning method based on Hausdorff under characteristic frequency bands specifically comprises the following steps:
step 1: fig. 1(a) is a model diagram of a power distribution network system grounded through arc suppression coils, and the length parameters of a feeder line of the power distribution network system are as follows: l1＝12km，l2＝15km，l3＝20km，l4＝9km，AB＝2km，CD＝1.5km，DE＝2km，EF＝2km。
Line distribution electrical parameters: l is1＝0.9297mH/km，C1＝0.07052μF/km L0＝4.1882mH/km，C00.0446 μ F/km. According to 10% compensation degree, namely L, of arc suppression coilpIn the feeder line L5, f is set to 0.81H, and the same section has different ground resistances at different times1-f5Single phase earth fault point (f)1If the main frequencies of transient zero-sequence free components of detection points on two sides of a fault point are the same or approximately the same, the correlation coefficient rho is larger, the criterion refuses to operate, and the point is a positioning blind area). Obtaining single-phase earth fault transient current data of a feeder according to a power distribution model, and firstly obtaining a 1-cycle comprehensive transient zero-sequence current discrete data matrix of an A node and a next-stage B node of a bus end of the feeder
Figure BDA0001878249920000051
And
Figure BDA0001878249920000052
step 2: selecting wavelet base dbn and decomposing into s layers, and decomposing the data of the two nodes (A and B) into frequency band information by utilizing a wavelet packet decomposition tool, wherein N is 10 and the number of decomposition layers s is 4 in consideration of the problems of smooth result, quick decomposition, signal energy concentration and the like.
And step 3: and (3) combining 15 frequency band information (non-fundamental wave) on the 4 th layer, selecting a characteristic frequency band of the A node of the bus terminal based on the wavelet packet energy maximum principle, wherein the characteristic frequency band self-adaptive selection process is shown in fig. 2, extracting the transient free component information of the characteristic frequency band and the current information of the same frequency band of the B node of the next level, namely the same frequency band of two nodes, as shown in fig. 3(a), and performing normalization processing, as shown in fig. 3 (B).
And 4, step 4: based on the normalized frequency band information, utilizing a Huasdorff distance algorithm to carry out matching degree optimization processing on the A, B node and obtaining the matching degree HSA→B。
Let the step length of single movement of data window be 1/fsThe width of the moving data is + -3 ms, and the step number of the left and right moving steps is N' ═ 3 × 10-3×fs30, the feeder section corresponding to the section switch serial number A is A → B, the number of the feeder section switches is 5, and the matching degree HSA→BComprises the following steps:
Figure BDA0001878249920000053
in the above formula, the first and second carbon atoms are,
Figure BDA0001878249920000054
and respectively node A and node B transient zero sequence current frequency band information normalization sequences.
And 5: comparison HSA→BSum criterion threshold HSsetIf HSA→B<HSsetThen the sector is a faulty sector. If HSA→B>HSsetThe sector is a normal sector. And determining the next section B → C, and circulating the steps 1 to 5 until the node of the end of the feeder line.
Step 1 to step 5 are executed, and the fault point f at different fault moments is obtained through traversal1-f5The traversal process of the positioning result under the grounding resistance and grounding mode is shown in fig. 4, however, the traversal result is shown in the following tables 1-8:
TABLE 1 simulation results of positioning method of ungrounded system at initial phase angle of fault of 0 °
Figure BDA0001878249920000055
Figure BDA0001878249920000061
TABLE 2 simulation results of positioning method of arc suppression coil grounding system at fault initial phase angle of 0 °
Figure BDA0001878249920000062
TABLE 3 simulation results of positioning method of ungrounded system at initial phase angle of fault of 30 °
Figure BDA0001878249920000071
TABLE 4 simulation results of positioning method of arc suppression coil grounding system at initial fault phase angle of 30 °
Figure BDA0001878249920000072
Figure BDA0001878249920000081
TABLE 5 simulation results of positioning method of ungrounded system at initial phase angle of fault of 60 °
Figure BDA0001878249920000082
TABLE 6 simulation results of positioning method of arc suppression coil grounding system at initial fault phase angle of 60 °
Figure BDA0001878249920000083
Figure BDA0001878249920000091
TABLE 7 simulation results of positioning method of ungrounded system at initial phase angle of fault of 90 °
Figure BDA0001878249920000092
TABLE 8 simulation results of positioning method of arc suppression coil grounding system at initial fault phase angle of 90 °
Figure BDA0001878249920000093
Figure BDA0001878249920000101
As can be seen from tables 1, 3, 5, 7 and tables 2, 4, 6, 8 respectively: when the system is not grounded and is grounded through the arc suppression coil, faults occur in different feeder line sections f under the conditions that the fault initial phase angles of 0 degrees, 30 degrees, 60 degrees and 90 degrees and the ground resistance are 0, 100, 500 and 1000 ohms1-f5Can be successfully positioned. The method for positioning the section is not influenced by the grounding mode and the grounding resistance of the system.
Tables 1 to 8 show that the simulation results depend on the simulation model of FIG. 1, and the fault point f on the feeder line L51The result shows that the positioning is correct at the fault blind area.

Claims (5)

1. A distribution network section positioning method based on Hausdorff under characteristic frequency bands is characterized by comprising the following steps:
step 1: transient current data meeting the requirements of wavelet packet decomposition and a Huasdorff distance algorithm are obtained according to the actual power distribution, and firstly, transient zero-sequence current data of 1 cycle wave at an x node and a next x +1 node of a feeder line bus end are obtained;
step 2: selecting wavelet base dbn and decomposing the wavelet base dbn into s layers, and decomposing the data of the two nodes into frequency band information by using a wavelet packet decomposition tool;
and step 3: bonding the s-th layer 2s-1 frequency band information, based on wavelet packet energy maximum principle, selecting characteristic frequency band of bus end x node, extracting characteristic frequency band transient free component information and next level x +1 node same frequency band current information, namely two nodes same frequency band, and making classificationPerforming normalization treatment;
and 4, step 4: based on the acquired normalized frequency band information, matching degree optimization processing is carried out on adjacent nodes by using a Huasdorff distance algorithm, and the matching degree HS is obtainedx→x+1；
And 5: comparison HSx→x+1Sum criterion threshold HSsetIf HSx→x+1<HSsetIf the section is a fault section; if HSx→x+1>HSsetIf the section is a normal section; and further determining the next section x +1 → x +2, and circulating the steps 1 to 5 until the node of the end of the feeder line.
2. The distribution network segment positioning method based on Hausdorff under the characteristic frequency band as claimed in claim 1, wherein: in the step 2, in order to eliminate the influence of different neutral point grounding modes on the fault positioning accuracy, a wavelet packet is used for carrying out frequency band decomposition, and the transient zero-sequence current obtained in the step 1 is decomposed into frequency band information of different frequency bands; wherein dbN and the number of decomposition layers s are selected as wavelet basis; considering the problems of smooth result, quick decomposition and signal energy concentration, selecting N to be 10; and s is 4.
3. The distribution network segment positioning method based on Hausdorff under the characteristic frequency band as claimed in claim 1, wherein: in the step 3, the band energy maximum principle is utilized to select 2sA characteristic frequency band in 1 frequency band information is shown as a formula (1), the selection principle depends on that the characteristic frequency band information contains fault transient zero-sequence current main frequency information, the amplitude of the main frequency information is maximum, the energy value is maximum, and normalization processing is carried out on the characteristic frequency band of the x node and the same frequency band information of the x +1 node;
let j equal 1,2,3, …, s; k is 1,2,3, …,2s(ii) a 1,2,3, …, wherein N is the number of sampling points of 0.5 cycle, and includes complete transient information after failure; s is the maximum number of layers of wavelet decomposition;
Figure FDA0002717823960000011
and
Figure FDA0002717823960000012
zero sequence current and energy of the xth section switch of the kth frequency band of the s layer are obtained, and the maximum value of x is K; k is a radical ofmaxIs s layer 2s1 frequency band serial number with maximum energy in the transient zero sequence current free component frequency band;
Figure FDA0002717823960000021
formula (1) is given by j 1,2,3, …, s, k 1,2,3, …,2s(ii) a 1,2,3, …, N; the sampling point number is 0.5 cycle, and the complete transient information after the fault is contained; s is the maximum number of layers of wavelet decomposition;
Figure FDA0002717823960000022
and
Figure FDA0002717823960000023
zero sequence current and energy of the xth section switch of the kth frequency band of the s layer are obtained, and the maximum value of x is K;
Figure FDA0002717823960000024
1,2 … 2 of s-th layer respectivelys-1,2sAn energy value of the frequency band; k is a radical ofmaxIs s layer 2sAnd 1 frequency band serial number with the maximum energy in the transient zero-sequence current free component frequency band.
4. The distribution network segment positioning method based on Hausdorff under the characteristic frequency band as claimed in claim 1, wherein: in the step 4, the matching degree optimization scheme adopts a data window translation method to eliminate;
let the step length of single movement of data window be 1/fsThe width of the moving data is +/-3 ms, and the maximum value of the total moving step number is N' ═ 3 × 10-3×fsThe feeder line section corresponding to the section switch serial number X is X → X +1, the number of the feeder line section switches is X, and the matching degree HSx→x+1Comprises the following steps:
Figure FDA0002717823960000025
in the formula (2), N is 0.5 cycle sampling points in the data window and contains complete transient information after the fault; n' is a movable step length;
Figure FDA0002717823960000026
respectively node x and x +1 transient zero-sequence current frequency band information normalization sequences;
in the data window length determination, in order to meet a matching degree optimization scheme, namely after the data window is ensured to move, the input data of the Haudorff distance algorithm can keep the same number of points N, so that a margin 2 x N' is required to be reserved in the data window; maximum error 3ms, f considering time synchronization modesThe margin can be determined as 100 sampling points through calculation, the length of the data window can be determined as 1 cycle, namely 50 sampling points are respectively expanded to the left and the right on the basis of the data of the N sampling points; the determination of the data window may be adjusted depending on engineering practices.
5. The distribution network segment positioning method based on Hausdorff under the characteristic frequency band as claimed in claim 1, wherein: in the step 4, a threshold setting method and an action criterion are constructed:
to ensure the reliability of the sector positioning, the ideal matching degree value HS is usedTReliability factor KrelA criterion threshold HS is setset(ii) a The threshold value is:
HSset＝HST/Krel
in the formula: krelTaking the mixture between 1.15 and 1.3; due to HSTNot to take K when being equal to 1rel＝1.2，KrelAccording to the actual engineering setting, combining the above formula to obtain HSset＝0.83；
If HSx→x+1<HSsetThe faulty section is x → x +1, otherwise, it is the normal section.
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