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 PDFInfo
- Publication number
- 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
- Authority
- CN
- China
- Prior art keywords
- distribution network
- power distribution
- frequency data
- phase
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 46
- 238000001228 spectrum Methods 0.000 claims abstract description 40
- 238000009825 accumulation Methods 0.000 claims abstract description 33
- 238000001514 detection method Methods 0.000 claims abstract description 30
- 230000009466 transformation Effects 0.000 claims abstract description 24
- 239000011159 matrix material Substances 0.000 claims description 38
- 238000004364 calculation method Methods 0.000 claims description 33
- 238000000819 phase cycle Methods 0.000 claims description 9
- 239000003990 capacitor Substances 0.000 description 6
- 238000012545 processing Methods 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000003044 adaptive effect Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 239000004020 conductor Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- 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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Theoretical Computer Science (AREA)
- Locating Faults (AREA)
- Testing Of Short-Circuits, Discontinuities, Leakage, Or Incorrect Line Connections (AREA)
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
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:
wherein ,for left positioning matrix LF t The t element of the x phase in>The method comprises the following steps:
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,t-th current in x-phase for feeder node p,>the t-th current in the x-phase for the feeder node q.
Optionally, the calculation formula of the right positioning matrix is:
wherein ,for right positioning matrix RI t The t element of the x phase in>The method comprises the following steps:
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,t-th voltage at x-phase for feeder node p,>t-th voltage at x-phase for feeder node q,>t-th current in phase a for feeder node p,>t-th current in phase b for feeder node p,>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.
Drawings
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.
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:
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:
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.
It can be understood that the calculation formula of the energy spectrum data es is:
the energy coefficient ec is calculated as:
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.
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.
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 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.
It can be understood that the calculation formula of the left positioning matrix is:
wherein ,for left positioning matrix LF t The t element of the x phase in>The method comprises the following steps:
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,t-th current in x-phase for feeder node p,>the t-th current in the x-phase for the feeder node q.
The calculation formula of the right positioning matrix is as follows:
wherein ,for right positioning matrix RI t The t element of the x phase in>The method comprises the following steps:
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,t-th voltage at x-phase for feeder node p,>t-th voltage at x-phase for feeder node q,>t-th current in phase a for feeder node p,>t-th current in phase b for feeder node p,>the t-th current in phase c for the feeder node p.
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 phaseAnd its zero sequence voltage->The phase relationship between them proceeds. If->Hysteresis->Single-phase earth fault occurs, lagging behind +.>Is a ground phase; />Advance ahead of->Two-phase ground fault occurs, +.>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:
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,for right positioning matrix RI t T element of x1 phase in ∈1->Left positioning matrix LF t T element of x1 phase in ∈1->For right positioning matrix RI t T element of the x2 phase in ∈,>for left positioning matrix LF t T element of the x2 phase in ∈,>for right positioning matrix RI t T element of x3 phase in ∈3,>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 and />And also 0.
For example: when a phase single-phase grounding occurs, x1=a fault location distance is:
when a bc phase short-circuit fault occurs, x1=b, x2=c, and the fault locating distance is:
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:
wherein ,for left positioning matrix LF t The t element of the x phase in>The method comprises the following steps:
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,t-th current in x-phase for feeder node p,>the t-th current in the x-phase for the feeder node q.
Further, the calculation formula of the right positioning matrix is:
wherein ,for right positioning matrix RI t The t element of the x phase in>The method comprises the following steps:
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,t-th voltage at x-phase for feeder node p,>t-th voltage at x-phase for feeder node q,>t-th current in phase a for feeder node p,>t-th current in phase b for feeder node p,>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:
wherein ,for left positioning matrix LF t The t element of the x phase in>The method comprises the following steps:
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:
wherein ,for right positioning matrix RI t The t element of the x phase in>The method comprises the following steps:
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,t-th voltage at x-phase for feeder node p,>t-th voltage at x-phase for feeder node q,>t-th current in phase a for feeder node p,>t-th current in phase b for feeder node p,>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.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111210767.3A CN113933749B (en) | 2021-10-18 | 2021-10-18 | Method, device, equipment and storage medium for detecting high-resistance ground fault of power distribution network |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111210767.3A CN113933749B (en) | 2021-10-18 | 2021-10-18 | Method, device, equipment and storage medium for detecting high-resistance ground fault of power distribution network |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113933749A CN113933749A (en) | 2022-01-14 |
CN113933749B true CN113933749B (en) | 2023-06-16 |
Family
ID=79279871
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202111210767.3A Active CN113933749B (en) | 2021-10-18 | 2021-10-18 | Method, device, equipment and storage medium for detecting high-resistance ground fault of power distribution network |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113933749B (en) |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
AU4547593A (en) * | 1992-07-10 | 1994-01-31 | RMIT Innovation Ltd | High impedance fault detector |
CN101187687A (en) * | 2007-12-21 | 2008-05-28 | 清华大学 | High resistance earthing fault detection method based on transient traveling wave |
CN101673930A (en) * | 2008-07-24 | 2010-03-17 | 通用电气公司 | Arc detection using discrete wavelet transforms |
CN104297636A (en) * | 2014-10-23 | 2015-01-21 | 广东电网有限责任公司电力科学研究院 | Pole-mounted distribution substation traveling wave detection method |
CN111487507A (en) * | 2020-06-01 | 2020-08-04 | 南方电网调峰调频发电有限公司西部检修试验分公司 | Power distribution network high-resistance fault identification method based on wavelet packet energy ratio |
CN112255492A (en) * | 2020-09-07 | 2021-01-22 | 西安理工大学 | Power distribution network single-phase grounding high-resistance fault identification method under strong noise background |
CN112505474A (en) * | 2020-10-30 | 2021-03-16 | 国网山东省电力公司聊城供电公司 | Fault positioning method and device based on phase current increment |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
AU2018241129B2 (en) * | 2017-10-27 | 2020-05-28 | Siemens Aktiengesellschaft | Method and detection device for detecting a high-impedance ground fault in an electrical energy supply network with a grounded neutral point |
-
2021
- 2021-10-18 CN CN202111210767.3A patent/CN113933749B/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
AU4547593A (en) * | 1992-07-10 | 1994-01-31 | RMIT Innovation Ltd | High impedance fault detector |
CN101187687A (en) * | 2007-12-21 | 2008-05-28 | 清华大学 | High resistance earthing fault detection method based on transient traveling wave |
CN101673930A (en) * | 2008-07-24 | 2010-03-17 | 通用电气公司 | Arc detection using discrete wavelet transforms |
CN104297636A (en) * | 2014-10-23 | 2015-01-21 | 广东电网有限责任公司电力科学研究院 | Pole-mounted distribution substation traveling wave detection method |
CN111487507A (en) * | 2020-06-01 | 2020-08-04 | 南方电网调峰调频发电有限公司西部检修试验分公司 | Power distribution network high-resistance fault identification method based on wavelet packet energy ratio |
CN112255492A (en) * | 2020-09-07 | 2021-01-22 | 西安理工大学 | Power distribution network single-phase grounding high-resistance fault identification method under strong noise background |
CN112505474A (en) * | 2020-10-30 | 2021-03-16 | 国网山东省电力公司聊城供电公司 | Fault positioning method and device based on phase current increment |
Non-Patent Citations (2)
Title |
---|
基于变异系数与高阶累积量的小电流接地故障选线;曾志辉等;《电力系统保护与控制》;第第48卷卷(第第13期期);第99-109页 * |
基于小波能量矩的高阻接地故障检测方法;朱晓娟等;《电力自动化设备》;第第36卷卷(第第12期期);第161-168页 * |
Also Published As
Publication number | Publication date |
---|---|
CN113933749A (en) | 2022-01-14 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CA2814661C (en) | Apparatus and method for fault detection and location determination | |
Jafarian et al. | High-speed superimposed-based protection of series-compensated transmission lines | |
CN112285601B (en) | Monopole ground fault line selection method for multi-terminal small-current grounding flexible direct current system | |
EP2686691A1 (en) | A method for detecting earth faults | |
EP3482472A1 (en) | A method and system for locating a fault in a mixed power transmission line | |
Kujur et al. | Detection of high impedance fault in distribution system considering distributed generation | |
de Alvarenga Ferreira et al. | A novel high impedance arcing fault detection based on the discrete wavelet transform for smart distribution grids | |
Guillen et al. | Hermite transform based algorithm for detection and classification of high impedance faults | |
CN113933749B (en) | Method, device, equipment and storage medium for detecting high-resistance ground fault of power distribution network | |
Dhend et al. | Efficient fault diagnosis in smart grid using non conventional mother wavelet function | |
CN104090211B (en) | A kind of online test method of distribution line high resistance earthing fault | |
CN106950465B (en) | Electric leakage detection and selection method and system for mine electric power network | |
Patel | Superimposed components of Lissajous pattern based feature extraction for classification and localization of transmission line faults | |
Santos et al. | High impedance fault detection and location based on electromagnetic transient analysis | |
US20220252644A1 (en) | Fault detection in an electric power system | |
CN113721114B (en) | High-resistance ground fault line selection method, system and storage medium for resonant ground power distribution network | |
Parikh et al. | Decision tree based fault classification scheme for protection of series compensated transmission lines | |
CN114062970B (en) | Low-current ground fault line selection method and device based on secondary power transformation system | |
CN113176478B (en) | Parallel arc detection method for low-voltage distribution network | |
Chen et al. | Arcing current features extraction using wavelet transform | |
Al_Kababjie et al. | A fault detection and classification using new distance relay | |
CN112630599A (en) | Low-current ground fault positioning method and system independent of voltage polarity | |
Zhang et al. | Single‐phase‐to‐ground fault feeder identification based on the feature between voltage and integration of current | |
Sultana et al. | Novel control methodology for detecting series arc in dc circuits | |
CN107561400B (en) | Distribution network short-circuit fault rapid detection method based on real-time wavelet transform |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |