CN113759278B - Ground fault line selection method suitable for small-current grounding system - Google Patents
Ground fault line selection method suitable for small-current grounding system Download PDFInfo
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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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
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Abstract
The invention discloses a grounding fault line selection method of a small-current grounding system, which comprises a starting judgment step and a fault line selection step, wherein the starting judgment step is used for monitoring transient fault signals of the small-current grounding system in real time, and starting the fault line selection step in time after a fault occurs; and the starting judgment step judges whether to enter the fault line selection step by comparing the transient state and steady state zero sequence voltage and the zero sequence voltage peak value of the power grid. The invention has the advantages that: the starting time of fault line selection is accurate and reliable, the fault line selection step can be started in time, and the fault line selection method is insensitive to the types of faults and mainly depends on fault characteristics. The fault condition is timely judged through the zero sequence voltage and the peak voltage, the fault line selection is timely entered, the fault branch is analyzed through the zero sequence current data near the fault moment at the fault moment, and the fault branch is rapidly and reliably given.
Description
Technical Field
The invention relates to the field of power grid detection, in particular to a ground fault line selection method of a low-current grounding system.
Background
Neutral point indirect grounding systems are generally adopted in power distribution networks of 35KV and below in China and are divided into resonance grounding systems and resistance grounding systems, and the resonance grounding systems and the resistance grounding systems are mainly used in urban power distribution networks of 10KV and below. The fault current in the indirect grounding mode is small when a single-phase grounding fault occurs, and the fault current has the characteristic of self-arc extinction, so that the fault current is also called a small-current grounding system. After the small current grounding fault occurs, the fault needs to be timely found and confirmed on the faulty branch, and fault line selection is completed, so that maintenance work can be conveniently carried out as soon as possible by maintenance staff. However, in the prior art, fault line selection is generally performed according to the power grid data after the fault occurs, and the time of fault line selection is relatively delayed, so that timely real-time fault line selection cannot be achieved.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a grounding fault line selection method of a low-current grounding system, which is used for matching fault line selection with fault occurrence time and timely entering the fault line selection to give an alarm.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: the ground fault line selection method based on the low-current ground system comprises a starting judgment step and a fault line selection step, wherein the starting judgment step is used for monitoring transient fault signals of the low-current ground system in real time, and starting the fault line selection step in time after a fault occurs; the fault line selection step is used for carrying out fault line selection through zero sequence current data of each branch of the power grid after receiving the starting signal to obtain a fault branch; and the starting judgment step judges whether to enter the fault line selection step by comparing the zero sequence voltage and the voltage peak value of the power grid.
The starting judging step comprises the following steps: when the zero sequence voltage U of the power grid 0 Greater than KU m When the fault line selection step is started, the line selection is carried out on the power grid fault through the fault line selection step; wherein K is less than 1 and greater than 0,U m Is the grid peak voltage.
K has a value of 0.15.
The fault line selection step comprises the step of immediately entering the fault line selection step when the zero sequence voltage is larger than a voltage peak value which is K times, taking the moment as a fault moment, and taking zero sequence current data near the fault moment as fault line selection data.
Taking m as the size of a sliding window, taking the midpoint of the sliding window as the fault moment, acquiring sub-sequences corresponding to the fault moment on a zero-sequence current time sequence, and calculating the sub-sequences of each branch and the zero-sequence current of each branchDistance of->And sequencing;
setting different threshold d th Dividing the branch into two classes A and B according to the distance threshold by adopting a dividing mode sp, wherein the classes A and B respectively refer to a fault class and a non-fault class;
respectively calculating different threshold values d th The information gain of each division mode is calculated, the division mode with the highest information gain is used as a fault line selection judging mode, the classification with the highest information gain is determined as a final judging mode of fault classification, the class A in the classification with the highest information gain is defined as a fault class, and the branch in the class A is defined as a fault branch.
The invention has the advantages that: the starting time of fault line selection is accurate and reliable, the fault line selection step can be started in time, and the fault line selection method is insensitive to the types of faults and mainly depends on fault characteristics. The fault condition is timely judged through the zero sequence voltage and the peak voltage, the fault line selection is timely entered, the fault branch is analyzed through the zero sequence current data near the fault moment at the fault moment, and the fault branch is rapidly and reliably given.
Drawings
The contents of the drawings and the marks in the drawings of the present specification are briefly described as follows:
FIG. 1 is a schematic view of a sliding window according to the present invention;
FIG. 2 is a flow chart of a fault classification method according to the present invention;
FIG. 3 is a single phase ground fault of a small resistance grounding system;
FIG. 4 is a circuit equivalent to a single-phase fault of a branch of a small-resistance grounding system;
FIG. 5 is a single-phase grounding equivalent circuit of a resonant grounding system;
FIG. 6 is a transient analysis equivalent circuit of single-phase earth fault;
Detailed Description
The following detailed description of the invention refers to the accompanying drawings, which illustrate preferred embodiments of the invention in further detail.
The system is grounded via a small resistor as shown in FIG. 3, wherein E A ,E B ,E C Respectively three-phase power supply electromotive forces, L 1 ...L n Respectively n outgoing lines of the system, C 01 ,...C 0n Respectively, are the branch circuits to the ground distributed capacitance R f Is the transition resistance of the fault point. In practice, the zero sequence impedance of the line is far higher than the positive sequence and negative sequence impedance, the impedance of the non-fault line is omitted, and the impedance of the fault line is classified into the transition resistance, so that the equivalent circuit shown in fig. 4 is obtained.
When in fault, the zero sequence voltage of the bus is as follows:
in the above-mentioned method, the step of,the sum of zero-sequence capacitance of the system to the ground; omega is the power frequency angular frequency.
The resonance grounding system is characterized in that an inductor is added between a neutral point of the system and the ground, when single-phase grounding faults occur, current flowing through the inductor effectively compensates capacitance current to the ground, so that the current flowing through the ground point is reduced, the ground arc of residual current is extinguished, and the arc is prevented from being further diffused. Meanwhile, due to the compensation effect of the arc suppression coil, the amplitude and the initial speed of the recovery voltage are reduced, the re-ignition of the arc and the generation of arc grounding overvoltage are inhibited, the system is prevented from being further developed into more serious multiphase or interphase short-circuit faults from single-phase short-circuit faults, and the power supply reliability of the system is improved.
A single-phase grounding equivalent circuit diagram of the resonant grounding system is shown in FIG. 3, wherein C 0 The capacitor is a relative ground capacitor, L is an arc suppression coil, and fault current of a ground point consists of an inductance current part and a capacitance current part.
In the middle ofFor earth fault current, +.>Inductive current flowing through the arc suppression coil, +.>Is the sum of the non-fault phase-to-ground capacitive currents.
The conventional second-order circuit simulates the transient process of a single-phase earth fault, as shown in fig. 4, C is the capacitance to ground of a three-phase line, L 0 Equivalent inductance R of power distribution network when neutral point is not grounded 0 Is the equivalent resistance of the stable resistance and the arc resistance when the fault point is grounded, r L Is the damping resistance of the arc suppression coil, L is the equivalent inductance of the arc suppression coil, u 0 Is equivalent zero sequence power supply voltage.
The ground fault line selection method of the low-current ground system comprises a starting judgment step and a fault line selection step, wherein the starting judgment step is used for monitoring fault signals of the low-current ground system in real time, and the fault line selection step is started in time after faults occur; the fault line selection step is used for carrying out fault line selection through zero sequence current data of each branch of the power grid after receiving the starting signal to obtain a fault branch; and the starting judgment step judges whether to enter the fault line selection step by comparing the zero sequence voltage and the voltage peak value of the power grid.
The starting judgment step comprises the following steps: when the zero sequence voltage U of the power grid 0 Greater than KU m When the fault line selection step is started, the power is turned on through the fault line selection stepSelecting lines for network faults; wherein K is less than 1 and greater than 0,U m For peak grid voltage, where K is preferably 0.15. When the fault is judged to occur, the fault line selection step is started immediately, so that the fault line selection is realized in time.
When the zero sequence voltage is greater than the voltage peak value of K times, the fault line selection step is immediately carried out, the moment is taken as the fault moment, and the zero sequence current data near the fault moment is taken as the fault line selection data.
Fault line selection is carried out by adopting zero sequence current flow data, and the high-dimensional flow data is defined as:
X＝[X (1) ，X (2) ，…，X (i) ，…，X (l) ] T in the above formula, l is the total branch number, and X is the zero sequence current set of all branches. The stream data of the ith branch in the formula is:
in the aboveAt t k And the value of the sampling point on the zero-sequence current of the ith branch at the moment.
And moving a sliding window on the stream data set by the step length of one sampling point, and calculating gains after the obtained window data set is used for calculating the distance and sorting the distance to judge fault classification. As shown in FIG. 1, which is a schematic diagram of a sliding window, the ith branch is at K t The window data of the time is:
in the formula (3), m is the size of a sliding window, the size of the sliding window directly influences the line selection result, and when the window is too small, the correct line selection can be influenced, and data acquisition is performed through the pre-calibrated window size T.
Middle K t The window data set of the time is:
taking m as the size of a sliding window, taking the midpoint of the sliding window as the fault moment, acquiring sub-sequences corresponding to the fault moment on a zero-sequence current time sequence, and calculating the sub-sequences of each branch and the zero-sequence current of each branchDistance of->And sequencing;
setting different threshold d th Dividing the branch into two classes A and B according to the distance threshold by adopting a dividing mode sp, wherein the classes A and B respectively refer to a fault class and a non-fault class;
respectively calculating different threshold values d th The information gain of each division mode is calculated, the division mode with the highest information gain is used as a fault line selection judging mode, the classification with the highest information gain is determined as a final judging mode of fault classification, the class A in the classification with the highest information gain is defined as a fault class, and the branch in the class A is defined as a fault branch.
First, for each time-sequential sub-sequence in the data acquired through the window, calculate its zero sequence current with each branchDistance of->And ordering. The Euclidean distance is generally used for calculating candidate segment C and zero sequence current +.>The distance between the two is calculated in a point-by-point mode, and the square of the difference is added and then square is obtained. And in the calculation, a subsequence with the length of w is taken from the zero sequence current of each branch, the distance between the subsequence and the candidate segment C is calculated, and finally, the minimum distance value is taken. Subsequent stepsThe sub-sequence C is a zero sequence current sub-sequence obtained by sampling on each branch.
On the basis of the sorting, a threshold d is set th According to the distance threshold, a division mode sp is adopted to divide the branch into two types A and B, and the two types A and B refer to a fault type and a non-fault type respectively.
And calculating the Information Gain of each division mode, and taking the division mode with the highest Information Gain as a fault line selection judging mode. A and B are fault class and non-fault class respectively, p (A) is probability distribution, m is total branch number, sp refers to division mode, entropy (I) is entropy under sp division mode,is the entropy of the undivided material. The information gain is calculated as follows:
zero sequence current setk＝1，...，m
entropy(I)＝＝-p(A)log(p(A))-p(B)log(p(B))
By comparing the information gains obtained in different division modes, we obtain a method for dividing the zero sequence current set of the unknown fault line into fault class and non-fault class. The distribution probability Pa may be calibrated in advance,
the classification effect is measured by the information gain. Then there are m distance values from the zero sequence current for each candidate segment. After ordering the distance values, the fault class and the non-fault class should be theoretically completely separated near a certain segmentation pointOpen, but in reality they may be staggered. We use the threshold d th The m distance values are divided into a fault class and a non-fault class. P (A) and P (B) are adopted to respectively represent the probability that the fault class and the non-fault class are correctly divided in an sp division mode, so that the division mode that each candidate segment can obtain the maximum information gain is calculated, and finally the candidate segment with the maximum information gain, namely the best classification effect, is selected. The entropy represents the degree of uncertainty of the information, and the difference between the entropy after division and the entropy before division is calculated to determine the division effect of this step. The pre-segmentation information is considered chaotic, theoretically- ≡, and for comparison, the algorithm actually takes 0.
In the fault line selection process, the fault line selection method adopts the shape algorithm, and training is carried out on the shape algorithm, because the process is to train the algorithm through zero sequence current when the fault line is known in historical data, namely searching for the optimal candidate segment and the optimal segmentation mode. After training is completed, namely candidate fragments and segmentation modes are found, only the corresponding candidate fragments are extracted when judging the fault category, euclidean distances between every two of the candidate fragments are calculated respectively, and fault lines and classification are determined through the selected segmentation modes.
During training, the collected zero sequence current historical data of each branch of the known fault line is subjected to filtering processing on zero sequence current waveforms of the branches in a wavelet filtering mode, noise interference is filtered, and denoised zero sequence current is obtainedCarrying out normalization treatment on the zero sequence current after denoising of all the branches; obtaining all possible subsequence sets on the zero sequence current time sequence by adopting a sliding window: candidate set candidate;
for each candidate subsequence C in candidate set candidate, calculating its and each path zero sequence currentDistance of->And sequencing; calculating candidate segment C and zero sequence current by Euclidean distance>Distance between
Setting a threshold d th According to the distance threshold, a division mode sp is adopted to divide the branch into two types A and B, and the two types A and B refer to a fault type and a non-fault type respectively.
K is the serial number of each branch
Setting different threshold d th Calculating Information Gain of each division mode, taking the division mode with the highest Information Gain as a fault line selection judging mode, determining the classification with the highest Information Gain as a final judging mode of fault classification, and defining class A in the classification with the highest Information Gain as a fault class, wherein branches in the class A are fault branches;
the information gain is calculated as follows:
zero sequence current setk＝1，...，m
entropy(I)＝-p(A)log(p(A))-p(B)log(p(B))
A and B are fault class and non-fault class respectively, p (A) is probability distribution, m is total branch number, sp refers to threshold d th The partitioning scheme, entopy (I), is the entropy in the sp partitioning scheme,entropy when not divided; and training the shape model algorithm by taking the classification threshold value and the classification mode which are obtained by the zero sequence current data of the fault line as the known number so as to determine the super-parameters in the algorithm model, so that the algorithm training is completed.
It is obvious that the specific implementation of the present invention is not limited by the above-mentioned modes, and that it is within the scope of protection of the present invention only to adopt various insubstantial modifications made by the method conception and technical scheme of the present invention.
Claims (3)
1. The ground fault classification method suitable for the low-current ground system is characterized by comprising the following steps of: the method comprises a starting judging step and a fault line selection step, wherein the starting judging step is used for monitoring fault signals of the low-current grounding system in real time, and starting the fault line selection step in time after faults occur; the fault line selection step is used for carrying out fault line selection through zero sequence current data of each branch of the power grid after receiving the starting signal to obtain a fault branch; the starting judging step judges whether to enter a fault line selection step by comparing the zero sequence voltage and the voltage peak value of the power grid;
the fault line selection step comprises the steps of immediately entering a fault line selection step when the zero sequence voltage is larger than a voltage peak value of K times, and taking zero sequence current data near the fault time as fault line selection data; taking m as the size of a sliding window, taking the midpoint of the sliding window as the fault moment, acquiring sub-sequences corresponding to the fault moment on a zero-sequence current time sequence, and calculating the sub-sequence C of each branch and the zero-sequence current of each branchDistance of->And sequencing;
setting different threshold d th Dividing the branch by a dividing method sp according to the distance thresholdThe method is divided into two types A and B, namely a fault type and a non-fault type;
respectively calculating different threshold values d th The information gain of each division mode is calculated, the division mode with the highest information gain is used as a fault line selection judging mode, the classification with the highest information gain is determined as a final judging mode of fault classification, the class A in the classification with the highest information gain is defined as a fault class, and the branch in the class A is defined as a fault branch.
2. A method of ground fault classification for use in a low current grounding system as claimed in claim 1, wherein: the starting judging step comprises the following steps: when the zero sequence voltage U of the power grid 0 Greater than KU m When the fault line selection step is started, the line selection is carried out on the power grid fault through the fault line selection step; wherein K is less than 1 and greater than 0,U m Is the grid peak voltage.
3. A method of ground fault classification for use in a low current grounding system as claimed in claim 2, wherein: k has a value of 0.15.
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