CN113933749B - Method, device, equipment and storage medium for detecting high-resistance ground fault of power distribution network - Google Patents

Method, device, equipment and storage medium for detecting high-resistance ground fault of power distribution network Download PDF

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CN113933749B
CN113933749B CN202111210767.3A CN202111210767A CN113933749B CN 113933749 B CN113933749 B CN 113933749B CN 202111210767 A CN202111210767 A CN 202111210767A CN 113933749 B CN113933749 B CN 113933749B
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distribution network
power distribution
frequency data
phase
data
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CN113933749A (en
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陈庆祺
白浩
何建宗
袁智勇
李伟峰
潘姝慧
余石成
雷金勇
陈学龙
郭琦
张驰
吴争荣
刘贯科
孙方坤
李旭
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CSG Electric Power Research Institute
Dongguan Power Supply Bureau of Guangdong Power Grid Co Ltd
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CSG Electric Power Research Institute
Dongguan Power Supply Bureau of Guangdong Power Grid Co 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
    • G01R31/50—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
    • G01R31/08—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
    • 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
    • G01R31/088—Aspects of digital computing
    • 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 application discloses a detection method, a device, equipment and a storage medium for high-resistance ground faults of a power distribution network, wherein the method comprises the following steps: performing discrete wavelet transformation on the acquired first voltage data of the power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data; acquiring energy spectrum data corresponding to the first high frequency data, a first threshold value, an energy coefficient corresponding to the first low frequency data and a second threshold value; when the energy spectrum data is larger than a first threshold value and the energy coefficient is smaller than a second threshold value, acquiring a plurality of second voltage data of the power distribution network to be detected; performing discrete wavelet transformation on each second voltage data to obtain a plurality of corresponding second high-frequency data; and judging whether the preset accumulation sum of the second high-frequency data is larger than a preset judgment index, and if so, judging that the power distribution network to be detected has high-resistance ground faults. The method solves the technical problems that the prior method for detecting the high-resistance ground fault of the power distribution network is easy to misjudge and misjudge during detection, thereby affecting the reliability of power supply.

Description

Method, device, equipment and storage medium for detecting high-resistance ground fault of power distribution network
Technical Field
The application relates to the technical field of power distribution networks, in particular to a method, a device, equipment and a storage medium for detecting high-resistance ground faults of a power distribution network.
Background
Single-phase high-resistance ground faults of non-ideal conductors, such as falling of wires on grasslands, roads, sand, ponds and the like, often occur in the power distribution network under the influence of factors such as natural environment, overhead distance of lines and the like. The high resistance ground accounts for about 10% of the total number of ground faults. If the high-resistance grounding fault exists for a long time, a new grounding point is generated due to overvoltage generated by the fault, the accident is further expanded, and even fire disaster is caused by electric arcs accompanied by the fault, so that personal and property safety is threatened, and the high-resistance grounding fault needs to be identified in time.
The existing detection of the high-resistance ground fault can be performed to a certain extent, but the normal operation and the high-resistance ground fault cannot be effectively distinguished during detection, misjudgment and misjudgment are easy to occur, and the power supply reliability is further affected.
Disclosure of Invention
In view of the above, the application provides a method, a device, equipment and a storage medium for detecting a high-resistance ground fault of a power distribution network, which solve the technical problems that the prior method for detecting the high-resistance ground fault of the power distribution network is easy to generate misjudgment and misjudgment during detection, thereby influencing the power supply reliability.
The first aspect of the present application provides a method for detecting a high-resistance ground fault of a power distribution network, including:
performing discrete wavelet transformation on the acquired first voltage data of the power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data;
acquiring energy spectrum data corresponding to the first high-frequency data, a first threshold value, an energy coefficient corresponding to the first low-frequency data and a second threshold value;
when the energy spectrum data is larger than the first threshold value and the energy coefficient is smaller than the second threshold value, acquiring a plurality of second voltage data of the power distribution network to be detected;
performing discrete wavelet transformation on each second voltage data to obtain a plurality of corresponding second high-frequency data;
and judging whether the preset accumulation sum of the second high-frequency data is larger than a preset judging index, if so, judging that the power distribution network to be detected has high-resistance ground fault, wherein the preset accumulation sum is the accumulation sum of the high-frequency data with preset layers in each second high-frequency data.
Optionally, the acquiring the energy spectrum data corresponding to the first high frequency data and the first threshold, and the energy coefficient corresponding to the first low frequency data and the second threshold specifically includes:
calculating corresponding energy spectrum data based on the first high frequency data, and calculating corresponding energy coefficients of the first low frequency data;
and calculating a corresponding first threshold value according to the energy spectrum data, and calculating a second threshold value according to the energy coefficient.
Optionally, the calculation formula corresponding to the first threshold is:
ρ＝(1+α).max(es)；
where ρ is a first threshold, α is a coefficient of expansion, and es is energy spectrum data.
Optionally, the calculation formula corresponding to the second threshold is:
τ＝(1-α).min(ec)；
where τ is a second threshold, α is the expansion coefficient, and ec is the energy coefficient.
Optionally, when it is determined that the power distribution network to be detected has a high-resistance ground fault, the method further includes:
acquiring three-phase voltages and three-phase currents respectively corresponding to any two adjacent feeder nodes in a power distribution network to be detected;
constructing a left positioning matrix and a right positioning matrix for fault positioning based on the three-phase voltages and the three-phase currents;
acquiring a fault type corresponding to the power distribution network to be detected and a fault positioning distance calculation formula corresponding to the fault type;
based on the fault location distance calculation formula, one of two feeder line nodes is taken as a reference point, and the fault location distance corresponding to the power distribution network to be detected is calculated according to the left location matrix and the right location matrix.
Optionally, the calculation formula of the left positioning matrix is:
Figure BDA0003308740690000021
wherein ,
Figure BDA0003308740690000031
for left positioning matrix LF t The t element of the x phase in>
Figure BDA0003308740690000032
The method comprises the following steps:
Figure BDA0003308740690000033
wherein x represents a phase sequence and is a, b and c; z xa ，z xb ，z xc Respectively, the impedance between x-phase and a, b, c, t represents the sample number,
Figure BDA0003308740690000034
t-th current in x-phase for feeder node p,>
Figure BDA0003308740690000035
the t-th current in the x-phase for the feeder node q.
Optionally, the calculation formula of the right positioning matrix is:
Figure BDA0003308740690000036
wherein ,
Figure BDA0003308740690000037
for right positioning matrix RI t The t element of the x phase in>
Figure BDA0003308740690000038
The method comprises the following steps:
Figure BDA0003308740690000039
wherein L represents the length of a line between feeder nodes p and q, x represents the phase sequence and is a, b and c; z xa ，z xb ，z xc Respectively, the impedance between x-phase and a, b, c, t represents the sample number,
Figure BDA00033087406900000310
t-th voltage at x-phase for feeder node p,>
Figure BDA00033087406900000311
t-th voltage at x-phase for feeder node q,>
Figure BDA00033087406900000312
t-th current in phase a for feeder node p,>
Figure BDA00033087406900000313
t-th current in phase b for feeder node p,>
Figure BDA00033087406900000314
the t-th current in phase c for the feeder node p.
The second aspect of the present application provides a detection apparatus for high-resistance ground fault of power distribution network, including:
the first transformation unit is used for performing discrete wavelet transformation on the acquired first voltage data of the power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data;
the first acquisition unit is used for acquiring the energy spectrum data corresponding to the first high frequency data, the first threshold value, the energy coefficient corresponding to the first low frequency data and the second threshold value;
the second acquisition unit is used for acquiring a plurality of second voltage data of the power distribution network to be detected when the energy spectrum data are larger than the first threshold value and the energy coefficient is smaller than the second threshold value;
the second transformation unit is used for carrying out discrete wavelet transformation on each second voltage data to obtain a plurality of corresponding second high-frequency data;
and the judging unit is used for judging whether the preset accumulation sum of the second high-frequency data is larger than a preset judging index, if so, judging that the power distribution network to be detected has high-resistance ground faults, wherein the preset accumulation sum is the accumulation sum of the high-frequency data with preset layers in each second high-frequency data.
The third aspect of the application provides a detection device for high-resistance ground faults of a power distribution network, which comprises a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the method for detecting a high-resistance ground fault of the power distribution network according to any one of the first aspects according to instructions in the program code.
A fourth aspect of the present application provides a storage medium, where the storage medium is configured to store program code, where the program code is configured to perform any one of the methods for detecting a high-resistance ground fault of a power distribution network according to the first aspect.
From the above technical scheme, the application has the following advantages:
the application provides a detection method of a high-resistance ground fault of a power distribution network, which comprises the steps of firstly carrying out discrete wavelet transformation on acquired first voltage data of the power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data, then acquiring energy spectrum data corresponding to the first high-frequency data and a first threshold value and energy coefficients corresponding to the first low-frequency data and a second threshold value, then acquiring a plurality of second voltage data of the power distribution network to be detected when the energy spectrum data is larger than the first threshold value and the energy coefficients are smaller than the second threshold value, then carrying out discrete wavelet transformation on each second voltage data to obtain a plurality of corresponding second high-frequency data, finally judging whether preset accumulated sums of the second high-frequency data are larger than preset judging indexes, and judging that the power distribution network to be detected has the high-resistance ground fault if the preset accumulated sums are accumulated sums of the high-frequency data preset in each second high-frequency data.
The inventor finds out after researching the prior art that the misjudgment and missed judgment of the prior detection method are that high-frequency data can be generated in normal operations such as switching operation, capacitor access and heavy-load switching, and the prior art only uses the high-frequency data to detect the high-resistance ground fault, so that the normal operation and the high-resistance ground fault cannot be effectively distinguished during detection, and therefore, the low-frequency data and the high-frequency data are adopted as judgment basis in the method, the normal operations such as voltage drop, switching operation, capacitor access and heavy-load switching and the high-resistance ground fault can be effectively distinguished, and the misjudgment and missed judgment of the high-resistance ground fault are avoided. Therefore, the technical problems that the conventional detection method for the high-resistance ground fault of the power distribution network is easy to misjudge and misjudge during detection, and the power supply reliability is affected are solved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic flow chart of a first embodiment of a method for detecting a high-resistance ground fault of a power distribution network according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a second embodiment of a method for detecting a high-resistance ground fault of a power distribution network according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a device for detecting a high-resistance ground fault of a power distribution network in an embodiment of the application.
Detailed Description
The embodiment of the application provides a detection method, a device, equipment and a storage medium for high-resistance ground faults of a power distribution network, which solve the technical problems that misjudgment and misjudgment easily occur during detection of the existing detection method for the high-resistance ground faults of the power distribution network, and further the power supply reliability is affected.
In order to make the present application solution better understood by those skilled in the art, the following description will clearly and completely describe the technical solution in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
An embodiment of a method for detecting a high-resistance ground fault of a power distribution network is provided in a first aspect of the present application.
Referring to fig. 1, a flow chart of a first embodiment of a method for detecting a high-resistance ground fault of a power distribution network according to an embodiment of the present application is shown.
The method for detecting the high-resistance ground fault of the power distribution network in the embodiment comprises the following steps:
and 101, performing discrete wavelet transformation on the acquired first voltage data of the power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data.
It is understood that the first voltage data in this embodiment is 1 cycle voltage signal. When the first voltage data is subjected to discrete wavelet transform, the first voltage data is subjected to m layers of discrete wavelet transform processing to respectively obtain m pieces of first high-frequency data h i And m first low frequency data l i . Specifically, when performing m-layer discrete wavelet transform processing, each layer of data is subjected to a high-pass filter to obtain high-frequency data, and a low-pass filter to obtain low-frequency data.
Step 102, energy spectrum data corresponding to the first high frequency data, a first threshold value, an energy coefficient corresponding to the first low frequency data and a second threshold value are obtained.
In this embodiment, the low frequency data and the high frequency data are both used as the judgment basis, so after the first high frequency data and the first low frequency data are obtained, the energy spectrum data and the first threshold value corresponding to the first high frequency data, and the energy coefficient and the second threshold value corresponding to the first low frequency data are calculated.
And 103, when the energy spectrum data is larger than a first threshold value and the energy coefficient is smaller than a second threshold value, acquiring a plurality of second voltage data of the power distribution network to be detected.
And when the energy spectrum data is larger than the first threshold value and the energy coefficient is smaller than the second threshold value, indicating that a potential high-resistance ground fault exists, otherwise, outputting a low-resistance ground fault and ending the judgment.
It can be understood that the second voltage data is also 1 cycle voltage signal, but in this embodiment, after obtaining that the power distribution network to be detected may have a high-resistance ground fault based on the first voltage data, for detection accuracy, the second detection is further performed based on the second voltage data.
In order to effectively identify the high-resistance ground fault, the second voltage data is acquired after a period of time after the first voltage data is acquired when the second voltage data is acquired because of a long period of fault generated by intermittent arc light. Specifically, the delay time may be set to 150ms, but may be other values, and those skilled in the art may select the delay time as needed.
The second voltage data number n may be set to 10, 20, or the like, and is not particularly limited in this embodiment.
And 104, performing discrete wavelet transformation on each second voltage data to obtain a plurality of corresponding second high-frequency data.
After n pieces of second voltage data are obtained, discrete wavelet transformation is carried out on each piece of second voltage data, and a plurality of pieces of second high-frequency data corresponding to each piece of second voltage data are obtained.
It will be appreciated that the discrete wavelet transform of the second voltage data may be performed in the same manner as the processing of the first voltage data, so that after the discrete wavelet transform of the second voltage data, each second voltage data corresponds to m second high frequency data
And 105, judging whether the preset accumulation sum of the second high-frequency data is larger than a preset judgment index, and if so, judging that the power distribution network to be detected has high-resistance ground faults.
In this embodiment, the preset accumulation sum is an accumulation sum of high frequency data of a preset number of layers in each second high frequency data. I.e. the sum of the high frequency data of the w-th layer of the m second high frequency data. It can be understood that, in this embodiment, w has a value of 4, and the corresponding calculation formula of the preset cumulative sum is:
Figure BDA0003308740690000071
wherein hif is a preset accumulation sum; h is a j4 The value of j is 1 for the 4 th layer high frequency data in the j second high frequency data，2，…，m。
And judging whether the preset accumulation sum of the second high-frequency data is larger than a preset judgment index, if so, indicating that the power distribution network to be detected has a high-resistance ground fault, otherwise, indicating that the power distribution network to be detected has a low-resistance ground fault.
In this embodiment, discrete wavelet transform is performed on first voltage data of an obtained power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data, then energy spectrum data corresponding to the first high-frequency data and a first threshold value, an energy coefficient corresponding to the first low-frequency data and a second threshold value are obtained, then when the energy spectrum data is greater than the first threshold value and the energy coefficient is smaller than the second threshold value, a plurality of second voltage data of the power distribution network to be detected are obtained, discrete wavelet transform is performed on each second voltage data to obtain a plurality of second high-frequency data corresponding to each second voltage data, finally, whether a preset accumulation sum of the second high-frequency data is greater than a preset judgment index is judged, if yes, high-resistance ground fault occurs in the power distribution network to be detected, and the preset accumulation sum is an accumulation sum of high-frequency data preset in each second high-frequency data. The embodiment adopts the low-frequency data and the high-frequency data as the judgment basis, can effectively distinguish normal operation such as voltage drop, switch operation, capacitor access, heavy-load switching and the like from high-resistance ground faults, and avoids misjudgment and missed judgment of the high-resistance ground faults. Therefore, the technical problems that the conventional detection method for the high-resistance ground fault of the power distribution network is easy to misjudge and misjudge during detection, and the power supply reliability is affected are solved.
The foregoing is a first embodiment of a method for detecting a high-resistance ground fault of a power distribution network provided by an embodiment of the present application, and the following is a second embodiment of a method for detecting a high-resistance ground fault of a power distribution network provided by an embodiment of the present application.
Referring to fig. 2, a flow chart of a second embodiment of a method for detecting a high-resistance ground fault of a power distribution network according to an embodiment of the present application is shown.
The method for detecting the high-resistance ground fault of the power distribution network in the embodiment comprises the following steps:
step 201, performing discrete wavelet transformation on the obtained first voltage data of the power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data.
It will be appreciated that the description of step 201 is the same as that of step 101 in the first embodiment, and specific reference may be made to the description of step 101, which is not repeated here.
Step 202, corresponding energy spectrum data is calculated based on the first high frequency data, and corresponding energy coefficients are calculated based on the first low frequency data.
It can be understood that the calculation formula of the energy spectrum data es is:
Figure BDA0003308740690000081
the energy coefficient ec is calculated as:
Figure BDA0003308740690000082
step 203, calculating a corresponding first threshold value according to the energy spectrum data, and calculating a second threshold value according to the energy coefficient.
The calculation formula corresponding to the first threshold value is as follows:
ρ＝(1+α).max(es)；
where ρ is a first threshold, α is an expansion coefficient, es is energy spectrum data, and max () represents a maximum value before the determination time, that is, the first threshold is an adaptive value, and is suitable for different fault environments.
The calculation formula corresponding to the second threshold value is as follows:
τ＝(1-α).min(ec)；
where τ is a second threshold, α is an expansion coefficient, ec is an energy coefficient, min () represents a minimum value before the determination time, that is, the second threshold is an adaptive value, and is suitable for different fault environments.
And 204, when the energy spectrum data is larger than a first threshold value and the energy coefficient is smaller than a second threshold value, acquiring a plurality of second voltage data of the power distribution network to be detected.
It is to be understood that the description of step 204 is the same as that of step 103 in the first embodiment, and specific reference may be made to the description of step 103, which is not repeated herein.
Step 205, performing discrete wavelet transform on each second voltage data to obtain a plurality of corresponding second high-frequency data.
It is to be understood that the description of step 205 is the same as that of step 104 in the first embodiment, and specific reference may be made to the description of step 104, which is not repeated herein.
And 206, judging whether the preset accumulation sum of the second high-frequency data is larger than a preset judgment index, and if so, judging that the power distribution network to be detected has high-resistance ground faults.
The preset accumulation sum is the accumulation sum of the high-frequency data with the preset layer number in each second high-frequency data.
It is to be understood that the description of step 206 is the same as that of step 105 in the first embodiment, and specific reference may be made to the description of step 105, which is not repeated herein.
Step 207, when it is determined that a high-resistance ground fault occurs in the power distribution network to be detected, three-phase voltages and three-phase currents corresponding to any two adjacent feeder nodes in the power distribution network to be detected are obtained.
The feeder nodes (tie switch, branch switch, segment switch) of the distribution network are provided with measurement terminals, and three-phase voltages and three-phase currents of any two adjacent feeder nodes (p, q) are collected respectively as follows
Figure BDA00033087406900000916
Figure BDA00033087406900000917
x represents a phase sequence and is a, b and c; ip, vp is the current and voltage of node P; iq, vq is the current and voltage of the q node; t represents the sampling number, the value is 1-T, and T is the total sampling point number.
Step 208, constructing a left positioning matrix and a right positioning matrix for fault positioning based on the three-phase voltage and the three-phase current.
It can be understood that the calculation formula of the left positioning matrix is:
Figure BDA0003308740690000091
wherein ,
Figure BDA0003308740690000092
for left positioning matrix LF t The t element of the x phase in>
Figure BDA0003308740690000093
The method comprises the following steps:
Figure BDA0003308740690000094
wherein x represents a phase sequence and is a, b and c; z xa ，z xb ，z xc Respectively, the impedance between x-phase and a, b, c, t represents the sample number,
Figure BDA0003308740690000095
t-th current in x-phase for feeder node p,>
Figure BDA0003308740690000096
the t-th current in the x-phase for the feeder node q.
The calculation formula of the right positioning matrix is as follows:
Figure BDA0003308740690000097
wherein ,
Figure BDA0003308740690000098
for right positioning matrix RI t The t element of the x phase in>
Figure BDA0003308740690000099
The method comprises the following steps:
Figure BDA00033087406900000910
wherein L represents the length of a line between feeder nodes p and q, x represents the phase sequence and is a, b and c; z xa ，z xb ，z xc Respectively, the impedance between x-phase and a, b, c, t represents the sample number,
Figure BDA00033087406900000911
t-th voltage at x-phase for feeder node p,>
Figure BDA00033087406900000912
t-th voltage at x-phase for feeder node q,>
Figure BDA00033087406900000913
t-th current in phase a for feeder node p,>
Figure BDA00033087406900000914
t-th current in phase b for feeder node p,>
Figure BDA00033087406900000915
the t-th current in phase c for the feeder node p.
Step 209, obtaining a fault type corresponding to the power distribution network to be detected and a fault locating distance calculation formula corresponding to the fault type.
For obtaining the specific type of the faults of the power distribution network to be detected, the single-phase and two-phase ground faults can be obtained by judging the maximum voltage phase
Figure BDA0003308740690000101
And its zero sequence voltage->
Figure BDA0003308740690000102
The phase relationship between them proceeds. If->
Figure BDA0003308740690000103
Hysteresis->
Figure BDA0003308740690000104
Single-phase earth fault occurs, lagging behind +.>
Figure BDA0003308740690000105
Is a ground phase; />
Figure BDA0003308740690000106
Advance ahead of->
Figure BDA0003308740690000107
Two-phase ground fault occurs, +.>
Figure BDA0003308740690000108
The non-faulty phase and the remaining two phases are faulty phases. For the three-phase short-circuit fault, whether the three-phase current is increased simultaneously or not and exceeds a preset value is detected, and if so, the three-phase short-circuit fault is judged to occur.
It can be understood that the general calculation formula of the fault location distance is:
Figure BDA0003308740690000109
wherein x1, x2, x3 represent faulty phases, which may be a, b, c, x1-x2-x3 represent faulty combinations, lo x1-x2-x3 For the fault location distance corresponding to the fault combination,
Figure BDA00033087406900001010
for right positioning matrix RI t T element of x1 phase in ∈1->
Figure BDA00033087406900001011
Left positioning matrix LF t T element of x1 phase in ∈1->
Figure BDA00033087406900001012
For right positioning matrix RI t T element of the x2 phase in ∈,>
Figure BDA00033087406900001013
for left positioning matrix LF t T element of the x2 phase in ∈,>
Figure BDA00033087406900001014
for right positioning matrix RI t T element of x3 phase in ∈3,>
Figure BDA00033087406900001015
for left positioning matrix LF t T element of x3 phase in (b).
For different fault types (i.e., fault combinations), there are different deformation formulas of the fault location distance calculation formula. Among them, for a three-phase distribution network, the following fault types are available:
(1) a phase is single-phase grounded; x1=a, x2=0, x3=0 (i.e., where 1 term is a and the other two terms are 0).
(2) b phase single-phase grounding; x1=b, x2=0, x3=0 (i.e., where 1 term is b and the other two terms are 0).
(3) c phase single-phase grounding; x1=c, x2=0, x3=0 (i.e., where 1 term is c and the other two terms are 0).
(4) a-b is short-circuited to ground; x1=a, x2=b, x3=0 (i.e., where 1 term is 0 and the other two terms are a, b).
(5) a-c is short-circuited to ground; x1=a, x2=c, x3=0 (i.e., where 1 term is 0 and the other two terms are a, c).
(6) c-b is short-circuited to ground; x1=c, x2=b, x3=0 (i.e., where 1 term is 0 and the other two terms are c, b).
(7) a-b-c three-phase short circuit; x1=a, x2=b, x3=c (i.e. 3 terms are a, b, c, respectively).
It will be appreciated that when the values of x1, x2, x3 are 0, the corresponding
Figure BDA00033087406900001016
and />
Figure BDA00033087406900001017
And also 0.
For example: when a phase single-phase grounding occurs, x1=a fault location distance is:
Figure BDA0003308740690000111
when a bc phase short-circuit fault occurs, x1=b, x2=c, and the fault locating distance is:
Figure BDA0003308740690000112
step 210, calculating the fault location distance corresponding to the power distribution network to be detected according to the left location matrix and the right location matrix by taking one of the two feeder line nodes as a reference point based on a fault location distance calculation formula.
It can be understood that the calculation of the fault location distance in this embodiment is applicable to the calculation of not only the high-resistance ground fault but also the corresponding fault location distance in the case of the low-resistance ground fault.
Compared with the prior art, the embodiment has the following advantages:
1) Meanwhile, the low-frequency component and the high-frequency component are adopted as judging characteristics, so that daily operations such as voltage drop, switching operation, capacitor access, heavy load switching and the like can be effectively distinguished, and misjudgment of high-resistance ground faults is avoided.
2) After judging the potential high-resistance grounding fault, delaying for a period of time to carry out secondary judgment, and effectively identifying the long-period fault of the high-resistance grounding fault caused by intermittent arc light
3) The proposed positioning algorithm (namely calculation of fault positioning distance) is not only suitable for low-resistance ground faults and high-resistance ground faults, but also suitable for different fault types, is not influenced by fault resistance and fault phases, and has universality.
In this embodiment, discrete wavelet transform is performed on first voltage data of an obtained power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data, then energy spectrum data corresponding to the first high-frequency data and a first threshold value, an energy coefficient corresponding to the first low-frequency data and a second threshold value are obtained, then when the energy spectrum data is greater than the first threshold value and the energy coefficient is smaller than the second threshold value, a plurality of second voltage data of the power distribution network to be detected are obtained, discrete wavelet transform is performed on each second voltage data to obtain a plurality of second high-frequency data corresponding to each second voltage data, finally, whether a preset accumulation sum of the second high-frequency data is greater than a preset judgment index is judged, if yes, high-resistance ground fault occurs in the power distribution network to be detected, and the preset accumulation sum is an accumulation sum of high-frequency data preset in each second high-frequency data. The embodiment adopts the low-frequency data and the high-frequency data as the judgment basis, can effectively distinguish normal operation such as voltage drop, switch operation, capacitor access, heavy-load switching and the like from high-resistance ground faults, and avoids misjudgment and missed judgment of the high-resistance ground faults. Therefore, the technical problems that the conventional detection method for the high-resistance ground fault of the power distribution network is easy to misjudge and misjudge during detection, and the power supply reliability is affected are solved.
The second aspect of the embodiment of the application provides an embodiment of a detection device for a high-resistance ground fault of a power distribution network.
Referring to fig. 3, a schematic structural diagram of a device for detecting a high-resistance ground fault of a power distribution network in an embodiment of the present application is shown.
The device for detecting a high-resistance ground fault of a power distribution network in this embodiment includes:
the first transformation unit is used for performing discrete wavelet transformation on the acquired first voltage data of the power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data;
the first acquisition unit is used for acquiring the energy spectrum data corresponding to the first high frequency data, the first threshold value, the energy coefficient corresponding to the first low frequency data and the second threshold value;
the second acquisition unit is used for acquiring a plurality of second voltage data of the power distribution network to be detected when the energy spectrum data are larger than a first threshold value and the energy coefficient is smaller than a second threshold value;
the second transformation unit is used for carrying out discrete wavelet transformation on each second voltage data to obtain a plurality of corresponding second high-frequency data;
and the judging unit is used for judging whether the preset accumulation sum of the second high-frequency data is larger than a preset judging index, if so, judging that the power distribution network to be detected has high-resistance ground faults, wherein the preset accumulation sum is the accumulation sum of the high-frequency data with preset layers in each second high-frequency data.
Further, the first acquisition unit specifically includes:
a first calculation subunit, configured to calculate corresponding energy coefficients based on the first high-frequency data and the corresponding energy spectrum data;
and the second calculating subunit is used for calculating a corresponding first threshold value and an energy coefficient according to the energy spectrum data to calculate a second threshold value.
Further, the calculation formula corresponding to the first threshold value is:
ρ＝(1+α).max(es)；
where ρ is a first threshold, α is a coefficient of expansion, and es is energy spectrum data.
Specifically, the calculation formula corresponding to the second threshold value is:
τ＝(1-α).min(ec)；
where τ is a second threshold, α is the expansion coefficient, and ec is the energy coefficient.
Further, the power distribution network high-resistance ground fault detection device in this embodiment further includes:
the third acquisition unit is used for acquiring three-phase voltages and three-phase currents respectively corresponding to any two adjacent feeder nodes in the power distribution network to be detected;
the construction unit is used for constructing a left positioning matrix and a right positioning matrix for fault positioning based on the three-phase voltage and the three-phase current;
the fourth acquisition unit is used for acquiring the fault type corresponding to the power distribution network to be detected and a fault positioning distance calculation formula corresponding to the fault type;
the calculation unit is used for calculating the fault location distance corresponding to the power distribution network to be detected by taking one of the two feeder line nodes as a reference point based on a fault location distance calculation formula according to the left location matrix and the right location matrix.
Optionally, the calculation formula of the left positioning matrix is:
Figure BDA0003308740690000131
wherein ,
Figure BDA0003308740690000132
for left positioning matrix LF t The t element of the x phase in>
Figure BDA0003308740690000133
The method comprises the following steps:
Figure BDA0003308740690000134
wherein x represents a phase sequence and is a, b and c; z xa ，z xb ，z xc Respectively, the impedance between x-phase and a, b, c, t represents the sample number,
Figure BDA0003308740690000135
t-th current in x-phase for feeder node p,>
Figure BDA0003308740690000136
the t-th current in the x-phase for the feeder node q.
Further, the calculation formula of the right positioning matrix is:
Figure BDA0003308740690000137
wherein ,
Figure BDA0003308740690000138
for right positioning matrix RI t The t element of the x phase in>
Figure BDA0003308740690000139
The method comprises the following steps:
Figure BDA00033087406900001310
wherein L represents the length of a line between feeder nodes p and q, x represents the phase sequence and is a, b and c; z xa ，z xb ，z xc Respectively, the impedance between x-phase and a, b, c, t represents the sample number,
Figure BDA00033087406900001311
t-th voltage at x-phase for feeder node p,>
Figure BDA00033087406900001312
t-th voltage at x-phase for feeder node q,>
Figure BDA00033087406900001313
t-th current in phase a for feeder node p,>
Figure BDA00033087406900001314
t-th current in phase b for feeder node p,>
Figure BDA00033087406900001315
the t-th current in phase c for the feeder node p.
In this embodiment, discrete wavelet transform is performed on first voltage data of an obtained power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data, then energy spectrum data corresponding to the first high-frequency data and a first threshold value, an energy coefficient corresponding to the first low-frequency data and a second threshold value are obtained, then when the energy spectrum data is greater than the first threshold value and the energy coefficient is smaller than the second threshold value, a plurality of second voltage data of the power distribution network to be detected are obtained, discrete wavelet transform is performed on each second voltage data to obtain a plurality of second high-frequency data corresponding to each second voltage data, finally, whether a preset accumulation sum of the second high-frequency data is greater than a preset judgment index is judged, if yes, high-resistance ground fault occurs in the power distribution network to be detected, and the preset accumulation sum is an accumulation sum of high-frequency data preset in each second high-frequency data. The embodiment adopts the low-frequency data and the high-frequency data as the judgment basis, can effectively distinguish normal operation such as voltage drop, switch operation, capacitor access, heavy-load switching and the like from high-resistance ground faults, and avoids misjudgment and missed judgment of the high-resistance ground faults. Therefore, the technical problems that the conventional detection method for the high-resistance ground fault of the power distribution network is easy to misjudge and misjudge during detection, and the power supply reliability is affected are solved.
A third aspect of the embodiments of the present application provides an embodiment of a detection device for a high-resistance ground fault of a power distribution network.
A detection device for high-resistance ground faults of a power distribution network comprises a processor and a memory; the memory is used for storing the program codes and transmitting the program codes to the processor; the processor is configured to perform the method for detecting a high-resistance ground fault of the power distribution network of the first aspect according to instructions in the program code.
A fourth aspect of the present embodiments provides an embodiment of a storage medium.
A storage medium for storing program code for performing the method of detecting a high-resistance ground fault of a power distribution network of the first aspect.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and units described above may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, e.g., the division of units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another grid network to be installed, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-only memory (ROM), a random access memory (RAM, randomAccessMemory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are merely for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims (10)

1. The utility model provides a detection method of high-resistance ground fault of power distribution network, which is characterized by comprising the following steps:
performing discrete wavelet transformation on the acquired first voltage data of the power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data;
acquiring energy spectrum data corresponding to the first high-frequency data, a first threshold value, an energy coefficient corresponding to the first low-frequency data and a second threshold value;
when the energy spectrum data is larger than the first threshold value and the energy coefficient is smaller than the second threshold value, acquiring a plurality of second voltage data of the power distribution network to be detected;
performing discrete wavelet transformation on each second voltage data to obtain a plurality of corresponding second high-frequency data;
and judging whether the preset accumulation sum of the second high-frequency data is larger than a preset judging index, if so, judging that the power distribution network to be detected has high-resistance ground fault, wherein the preset accumulation sum is the accumulation sum of the high-frequency data with preset layers in each second high-frequency data.
2. The method for detecting a high-resistance ground fault of a power distribution network according to claim 1, wherein the step of acquiring the energy spectrum data and the first threshold value corresponding to the first high-frequency data and the energy coefficient and the second threshold value corresponding to the first low-frequency data specifically comprises:
calculating corresponding energy spectrum data based on the first high frequency data, and calculating corresponding energy coefficients of the first low frequency data;
and calculating a corresponding first threshold value according to the energy spectrum data, and calculating a second threshold value according to the energy coefficient.
3. The method for detecting a high-resistance ground fault of a power distribution network according to claim 2, wherein the calculation formula corresponding to the first threshold value is as follows:
ρ＝(1+α).max(es)；
where ρ is a first threshold, α is a coefficient of expansion, and es is energy spectrum data.
4. The method for detecting a high-resistance ground fault of a power distribution network according to claim 2, wherein the calculation formula corresponding to the second threshold value is:
τ＝(1-α).min(ec)；
where τ is a second threshold, α is the expansion coefficient, and ec is the energy coefficient.
5. The method for detecting a high-resistance ground fault in a power distribution network according to claim 1, wherein when it is determined that the high-resistance ground fault occurs in the power distribution network to be detected, the method further comprises:
acquiring three-phase voltages and three-phase currents respectively corresponding to any two adjacent feeder nodes in a power distribution network to be detected;
constructing a left positioning matrix and a right positioning matrix for fault positioning based on the three-phase voltages and the three-phase currents;
acquiring a fault type corresponding to the power distribution network to be detected and a fault positioning distance calculation formula corresponding to the fault type;
based on the fault location distance calculation formula, one of two feeder line nodes is taken as a reference point, and the fault location distance corresponding to the power distribution network to be detected is calculated according to the left location matrix and the right location matrix.
6. The method for detecting a high-resistance ground fault of a power distribution network according to claim 5, wherein the calculation formula of the left positioning matrix is:
Figure FDA0003308740680000021
wherein ,
Figure FDA0003308740680000022
for left positioning matrix LF t The t element of the x phase in>
Figure FDA0003308740680000023
The method comprises the following steps:
Figure FDA0003308740680000024
wherein x represents a phase sequence and is a, b and c; z xa ，z xb ，z xc Respectively, the impedance between x-phase and a, b, c, t represents the sample number,
Figure FDA0003308740680000025
t-th current in x-phase for feeder node p,>
Figure FDA0003308740680000026
the t-th current in the x-phase for the feeder node q.
7. The method for detecting a high-resistance ground fault of a power distribution network according to claim 5, wherein the calculation formula of the right positioning matrix is:
Figure FDA0003308740680000027
wherein ,
Figure FDA0003308740680000028
for right positioning matrix RI t The t element of the x phase in>
Figure FDA0003308740680000029
The method comprises the following steps:
Figure FDA00033087406800000210
wherein L represents the length of a line between feeder nodes p and q, x represents the phase sequence and is a, b and c; z xa ，z xb ，z xc Respectively, the impedance between x-phase and a, b, c, t represents the sample number,
Figure FDA00033087406800000211
t-th voltage at x-phase for feeder node p,>
Figure FDA00033087406800000212
t-th voltage at x-phase for feeder node q,>
Figure FDA00033087406800000213
t-th current in phase a for feeder node p,>
Figure FDA00033087406800000214
t-th current in phase b for feeder node p,>
Figure FDA00033087406800000215
the t-th current in phase c for the feeder node p.
8. The utility model provides a detection device of distribution network high resistance ground fault which characterized in that includes:
the first transformation unit is used for performing discrete wavelet transformation on the acquired first voltage data of the power distribution network to be detected to obtain a plurality of first high-frequency data and first low-frequency data;
the first acquisition unit is used for acquiring the energy spectrum data corresponding to the first high frequency data, the first threshold value, the energy coefficient corresponding to the first low frequency data and the second threshold value;
the second acquisition unit is used for acquiring a plurality of second voltage data of the power distribution network to be detected when the energy spectrum data are larger than the first threshold value and the energy coefficient is smaller than the second threshold value;
the second transformation unit is used for carrying out discrete wavelet transformation on each second voltage data to obtain a plurality of corresponding second high-frequency data;
and the judging unit is used for judging whether the preset accumulation sum of the second high-frequency data is larger than a preset judging index, if so, judging that the power distribution network to be detected has high-resistance ground faults, wherein the preset accumulation sum is the accumulation sum of the high-frequency data with preset layers in each second high-frequency data.
9. The utility model provides a detection equipment of distribution network high resistance ground fault which characterized in that includes treater and memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the method for detecting a high-resistance ground fault of a power distribution network according to any one of claims 1 to 7 according to instructions in the program code.
10. A storage medium for storing program code for performing the method of detecting a high-resistance ground fault of an electrical distribution network according to any one of claims 1 to 7.
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