CN114325240A - Fault line identification method based on high-frequency fault information energy evaluation - Google Patents
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Abstract
The invention provides a fault line identification method based on high-frequency fault information energy evaluation, which is characterized in that a high-frequency transient traveling wave process during single-phase earth fault of a low-current grounding system is analyzed, and a plurality of first principal components are selected according to the accumulated contribution rate of each principal component, so that the information of original variables is better retained. And further providing a fault line identification algorithm based on principal component analysis. Starting from the essential characteristics of the high-frequency signals, the method is favorable for accurately grasping the fundamental characteristics of the fault, and greatly improves the fault line identification accuracy based on high-frequency information.
Description
Technical Field
The invention relates to the field of line fault identification, in particular to a fault line identification method based on high-frequency fault information energy evaluation.
Background
The most widely used neutral grounding methods in modern power systems are direct grounding, non-grounding and arc suppression coil grounding, and for medium voltage power systems of 66kv and below, lowering the insulation level becomes a relatively minor factor, and other factors affecting the grounding method become major considerations for selecting the grounding method. In this case, different grounding methods are used, starting from different points of view and from a particular problem. Typical grounding means for power distribution networks are ungrounded, grounded via a crowbar coil, grounded via a low resistance or grounded via a low reactance. A non-effective grounding mode is widely adopted in a power distribution network system in China, and comprises a neutral point which is not grounded, and is grounded through an arc suppression coil and a high resistance, so that the power distribution network system can continuously run for 1-2 hours without immediate tripping when a single-phase grounding fault occurs, and the power supply reliability is greatly improved. But single-phase ground fault routing and localization becomes a difficult problem. The conventional line selection method cannot meet the production requirement, and further research on rapid line fault identification is urgently needed.
At present, the reason that the problem of line selection protection is difficult to solve is complex, and firstly, the fault condition is complex, and the fault condition can be stable fault or discontinuous fault, and can also be resistance fault or arc fault. The fault conditions are different, and the generated fault amount is greatly different in value and change rule; especially some unstable intermittent faults, the waveform is very irregular. Secondly, the single-phase grounding fault current of the non-effective grounding power grid is only network grounding capacitance current, the numerical value is very small, the fault current may be lower than the lower limit value of the current transformer range under some conditions, and the measurement error is very large. For the power grid with a larger grounding current, an arc suppression coil needs to be arranged, and the difficulty of line selection protection of the arc suppression coil grounding power grid is higher.
The signal-to-noise ratio of the detected fault signal is very low due to the amplification effect of the field electromagnetic interference and the zero sequence loop on higher harmonics and various transient quantities. For an overhead line, a zero sequence current filter is needed to obtain zero sequence current, unbalanced current exists in the zero sequence current filter, and zero sequence current is generated due to unbalance of a primary power grid. These additional currents are superimposed on the weak fault currents and are not easily separated out.
Disclosure of Invention
The invention provides a fault line identification method based on high-frequency fault information energy evaluation, which starts from essential characteristics of high-frequency signals, is favorable for accurately grasping fundamental characteristics of faults and greatly improves the fault line identification accuracy based on high-frequency information.
The method comprises the following steps:
s101, analyzing characteristic data of a traveling wave transmission process;
s102, analyzing and evaluating wave energy main components;
s103, taking analysis and evaluation data of wave energy main components as line selection criteria;
the line selection criterion comprises the following steps:
(1) acquiring fault traveling wave signals of outgoing lines by using a traveling wave acquisition device and acquiring zero-mode components;
(2) calculating an expression E' representing the energy of the traveling wave signal;
(3) and calculating the principal components of the wave energy of each outgoing line according to the expression dF, and determining a fault line according to the values of the principal components of the wave energy.
In the invention, analysis and evaluation data of wave energy main components are used as a line selection criterion in the steps:
when a fault traveling wave signal appears, a signal curve becomes irregular; and with the time backward shift, the dimension of the sampling point gradually increases, and when the dimension reaches the peak value, the fault signal starts to enter a relatively stable state.
In step S101 of the present invention,
provided with a line L1When the fault occurs at the moment t, MB is one of the non-fault lines, and n outgoing lines are arranged on a line bus;
setting the initial traveling wave of the non-fault line as iufThe initial traveling wave of the fault line is ifMeasuring the initial traveling wave to be i at the bus end of the fault linefSuperposition with the reflected wave at the fault point, denoted iffThen, there are:
where γ and ρ are the refraction and reflection coefficients of the traveling wave, respectively, then:
in the formula ZcZero mode wave impedance is equal, Z2For looking into the equivalent impedance of the bus terminal from the fault line, when there are n outgoing lines at the bus terminal, Z2＝Zc(n-1), it is possible to obtain:
in step S102 of the present invention,
according to the traveling wave signal theory, i (t) is set at t0The energy E for the time period t is defined as follows:
accordingly, for discrete sample values, E is calculated as:
the traveling wave signal energy E' is characterized by N traveling wave signal extreme values:
in the formula SpiIs a traveling wave signal extreme value;
transforming multivariable into few principal components by dimension reduction, configuring a group of data, wherein the total number of the data is n, each sample has p evaluation indexes to form an n multiplied by p matrix,
wave energy principal component analysis combines the observed variables into p principal components:
the variance based on each principal component F is decreasing, with the differential expression:
is provided with [ tk-t，tk]The interval signal comprises an even number n of sampling points (x)1 (k)…,xn (k)) Let us order
And
N(k)(Δ)＝D(k)(Δ)/Δ
N(k)(2Δ)＝D(k)(2Δ)/2Δ
in the formula N(k)(Delta) and N(k)(2 Delta) is Delta and 2 Delta is in the time interval of [ tk-t，tk]The equivalent number of the above energies;
obtaining an expression of principal component F as
And reducing the dimension of the guided wave signal characteristics based on a wave energy principal component analysis mode to obtain a signal characteristic principal component comprehensive score and obtain the corresponding relation between the signal characteristic principal component comprehensive score and a fault line.
According to the technical scheme, the invention has the following advantages:
according to the fault line identification method based on high-frequency fault information energy evaluation, the high-frequency transient traveling wave process during single-phase earth fault of the low-current grounding system is analyzed, the former multiple principal components are selected according to the accumulated contribution rate of each principal component, and the information of the original variable is better reserved. And further providing a fault line identification algorithm based on principal component analysis. Starting from the essential characteristics of the high-frequency signals, the method is favorable for accurately grasping the fundamental characteristics of the fault, and greatly improves the fault line identification accuracy based on high-frequency information.
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In order to more clearly illustrate the technical solution of the present invention, the drawings used in the description will be briefly introduced, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a flow chart of a combined route selection criterion;
FIG. 2 is a flow chart of principal component analysis of wave energy;
FIG. 3 is a low current map;
FIG. 4 is a schematic view of a fault traveling wave catadioptric diagram;
FIG. 5 is a voltage waveform diagram;
FIG. 6 is a fault line waveform diagram;
FIG. 7 is a non-fault line waveform diagram;
FIG. 8 is a diagram of zero-mode components and corresponding energy analysis of fault traveling wave signals of each outlet of a bus;
fig. 9 is a graph showing the results of principal component analysis of each line.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1 to 3, the present invention provides a fault line identification method based on high-frequency fault information energy evaluation, the method comprising:
s101, analyzing characteristic data of a traveling wave transmission process;
the low current grounding system wiring is shown in fig. 3. Provided with a line L1At time t, when there is a fault, as shown in fig. 4, MB is one of the non-faulty lines, and n outgoing lines are provided for the line bus.
Setting the initial traveling wave of the non-fault line as iufThe initial traveling wave of the fault line is ifMeasuring the initial traveling wave to be i at the bus end of the fault linefSuperposition with reflected waves at the fault point, denoted iffThen, there are:
where γ and ρ are the refraction and reflection coefficients of the traveling wave, respectively, then:
in the formula ZcZero mode wave impedance is equal, Z2For looking into the equivalent impedance of the bus terminal from the fault line, when there are n outgoing lines at the bus terminal, Z2＝Zc(n-1), it is possible to obtain:
in an actual small-current grounding system, the value of n is larger, and the amplitude of the initial traveling wave of the fault line measured by the obtained bus end is far larger than that of the non-fault line. However, the wave head of the initial line needs to be identified in the actual signal, the amplitude measurement may have the problems of poor precision and the like, and the criterion only depending on the initial wave head has unreliability. Therefore, if the energy of the initial wave head is introduced, the property of the initial wave head is judged by using the traveling wave energy evaluation method, and then the fault identification method is provided, so that the method has obvious feasibility and improves the reliability of the criterion.
S102, analyzing and evaluating wave energy main components;
(1) representation of traveling wave energy
According to the traveling wave signal theory, i (t) is set at t0The energy E for the time period t is defined as follows:
accordingly, for discrete sample values, E is calculated as:
it can be seen that the extreme value of the traveling wave signal can represent the energy of the signal. In order to reduce the calculation amount, N traveling wave signal extreme values are used for representing traveling wave signal energy E':
in the formula SpiIs a traveling wave signal extremum.
(2) Wave energy principal component analysis method
The wave energy principal component analysis utilizes dimensionality reduction to convert multivariable into few principal components, aims to describe original data by using fewer features, converts high-correlation features into mutually independent or uncorrelated features and uses the mutually independent or uncorrelated features as a comprehensive index for characterizing data. For a group of data, n samples are provided, each sample has p evaluation indexes, an n multiplied by p matrix is formed,
wave energy principal component analysis combines the observed variables into p principal components:
since the variance of each principal component F is decreasing, its differential expression is as follows:
is provided with [ tk-t，tk]The interval signal comprises an even number n of sampling points (x)1 (k)…,xn (k)) Let us order
And
N(k)(Δ)＝D(k)(Δ)/Δ
N(k)(2Δ)＝D(k)(2Δ)/2Δ
in the formula N(k)(Delta) and N(k)(2 Delta) is Delta and 2 Delta is in the time interval of [ tk-t，tk]The equivalent number of energies above.
From this, an expression of principal component F is obtained as
In the invention, the first m principal components are selected according to the magnitude of the accumulated contribution rate of each principal component, and when the accumulated contribution rate of the principal components reaches more than 85 percent, the comprehensive variables can be ensured to comprise most of information of the original variables. The fault traveling wave signal is complex, and when the mathematical model is adopted for expression, the detection can be effectively carried out by replacing the single signal characteristic with the multi-signal characteristic, so that the detection precision and reliability can be improved. Meanwhile, the wave energy principal component analysis method carries out dimension reduction on the guided wave signal characteristics to obtain the signal characteristic principal component comprehensive score, and the principal component is synthesized to obtain the corresponding relation between the principal component and a fault line.
S103, taking analysis and evaluation data of wave energy main components as line selection criteria;
the wave energy principal component analyzes the singularity of the signal, and the size of the signal reflects the complexity of the signal mutation position. As can be seen from fig. 1, when a fault traveling wave signal occurs, the signal curve becomes complex; and with the time backward shift, the dimension of the sampling point gradually increases, and when the dimension reaches the peak value, the fault signal starts to enter a relatively stable state.
The wave energy principal component analysis signal criterion steps are shown in fig. 2:
(1) acquiring fault traveling wave signals of all outgoing lines by using a traveling wave acquisition device and acquiring zero-mode components of the fault traveling wave signals;
(2) calculating an expression E' representing the energy of the traveling wave signal;
(3) and calculating the main component of each outgoing line wave energy by an expression dF. And determining a fault line through the wave energy principal component value.
The invention also carries out simulation research on the fault line identification method based on the high-frequency fault information energy evaluation, and verifies the effectiveness of the method by using Simulink as shown in figures 5 to 9. The 35kV bus is provided with 5 feeder lines which are numbered as L1, L2, L3, L4 and L5 in sequence, and the lengths of the feeder lines are 24km, 10km, 17km, 36km and 31km respectively. The positive sequence parameter and the zero sequence parameter of the line are respectively as follows:
R1＝0.46.，X1＝0.56.,C1＝0.1μF/km；
R0＝0.73,X0＝1.25,C0＝0.04μF/km。
(1) simulation example 1: the neutral point is not grounded, the grounding resistance is 25 omega, and the closing phase angle is 46 degrees. The original recording waveform of the fault is shown in fig. 5 to 7. And respectively taking the N values as 5, 7 and 9 to calculate the outgoing lines E', as shown in FIG. 8, and combining the main component analysis corresponding to the outgoing line traveling wave signals of the buses, as shown in FIG. 9, further confirming the line selection result to obtain a fault line L1.
TABLE 1 data processing results
(2) Simulation example 2: the neutral point is not grounded, the grounding resistance is 1000 omega, and the closing phase angle is 70 degrees. The traveling wave signal is weak at this time, and the simulation result is shown in table 2. At the moment, the fault line can still be effectively obtained according to the principal component analysis and judgment.
TABLE 2 high resistance Fault results
(3) Simulation example 3: the neutral point is not grounded, the fault grounding resistance is 15 omega, and the voltage zero-crossing time is faulted. The traveling wave signal is weak, and the principal component contribution ratio is shown in table 3.
TABLE 3 principal component contribution and cumulative contribution (simulation)
(4) Simulation example 4: the neutral point is grounded through the arc suppression coil, the fault ground resistance is 15 Ω, the closing phase angle is 40 °, and the data is shown in table 5.
Table 5 arc suppression coil grounding results
The fault line identification method based on high-frequency fault information energy assessment provided by the invention is combined with the units and algorithm steps of each example described in the embodiment disclosed in the text, and can be realized by electronic hardware, computer software or the combination of the two. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
Those skilled in the art will appreciate that various aspects of the fault line identification method based on high frequency fault information energy assessment provided by the present invention may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (4)
1. A fault line identification method based on high-frequency fault information energy assessment is characterized by comprising the following steps:
s101, analyzing characteristic data of a traveling wave transmission process;
s102, analyzing and evaluating wave energy main components;
s103, taking analysis and evaluation data of wave energy main components as line selection criteria;
the line selection criterion comprises the following steps:
(1) acquiring fault traveling wave signals of outgoing lines by using a traveling wave acquisition device and acquiring zero-mode components;
(2) calculating an expression E' representing the energy of the traveling wave signal;
(3) and calculating the principal components of the wave energy of each outgoing line according to the expression dF, and determining a fault line according to the values of the principal components of the wave energy.
2. The faulty line identification method based on high-frequency fault information energy assessment according to claim 1,
in the step, analysis and evaluation data of wave energy main components are taken as a line selection criterion:
when a fault traveling wave signal appears, a signal curve becomes irregular; and with the time backward shift, the dimension of the sampling point gradually increases, and when the dimension reaches the peak value, the fault signal starts to enter a relatively stable state.
3. The faulty line identification method based on high-frequency fault information energy assessment according to claim 1, characterized in that, in step S101,
provided with a line L1Defining MB as one non-fault line when the fault occurs at the moment t, and setting a line bus to have n outgoing lines;
setting the initial traveling wave of the non-fault line as iufThe initial traveling wave of the fault line is ifMeasuring the initial traveling wave to be i at the bus end of the fault linefSuperposition with the reflected wave at the fault point, denoted iffThen, there are:
where γ and ρ are the refraction and reflection coefficients of the traveling wave, respectively, then:
in the formula ZcZero mode wave impedance is equal, Z2For looking into the equivalent impedance of the bus terminal from the fault line, when there are n outgoing lines at the bus terminal, Z2＝Zc(n-1), it is possible to obtain:
4. the faulty line identification method based on high-frequency fault information energy assessment according to claim 1, wherein in step S102,
according to the traveling wave signal theory, i (t) is set at t0The energy E for the time period t is defined as follows:
accordingly, for discrete sample values, E is calculated as:
the traveling wave signal energy E' is characterized by N traveling wave signal extreme values:
in the formula SpiIs a traveling wave signal extreme value;
transforming multivariable into few principal components by dimension reduction, configuring a group of data, wherein the total number of the data is n, each sample has p evaluation indexes to form an n multiplied by p matrix,
wave energy principal component analysis combines the observed variables into p principal components:
the variance based on each principal component F is decreasing, with the differential expression:
is provided with [ tk-t，tk]The interval signal comprises an even number n of sampling points (x)1 (k)…,xn (k)) Let us order
And
N(k)(Δ)＝D(k)(Δ)/Δ
N(k)(2Δ)＝D(k)(2Δ)/2Δ
in the formula N(k)(Delta) and N(k)(2 Delta) is Delta and 2 Delta is in the time interval of [ tk-t，tk]The equivalent number of the above energies;
obtaining an expression of principal component F as
And reducing the dimension of the guided wave signal characteristics based on a wave energy principal component analysis mode to obtain a signal characteristic principal component comprehensive score and obtain the corresponding relation between the signal characteristic principal component comprehensive score and a fault line.
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