CN111695089A - Alternating current transmission line fault identification method based on multi-fractal spectrum - Google Patents

Abstract

The invention discloses an alternating current transmission line fault identification method based on a multi-fractal spectrum, which comprises the steps of firstly reading phase voltage obtained by a high-speed acquisition device at a measuring end, and solving a voltage fault component in a 5ms time window according to a superposition principle; then calculating the mass distribution probability P of the voltage fault component_i() Calculating the maximum value α of the singularity index α according to the multi-fractal theory_maxAnd minimum value α_minFinally, the difference delta α between the maximum value and the minimum value is used for carrying out the inside and outside fault identification, if any one phase or multiple phases of voltage fault components meet the conditions that delta α is more than delta α_setIf the three-phase voltage fault components meet the condition that delta α is less than or equal to delta α_setAnd judging the fault as an out-of-area fault. The method of the invention can quickly and accurately identify the internal fault and the external fault。

Description

Alternating current transmission line fault identification method based on multi-fractal spectrum

Technical Field

The invention relates to the technical field of power system relay protection, in particular to an alternating current transmission line fault identification method based on a multi-fractal spectrum.

Background

On one hand, because the scale of the power system is continuously enlarged, more and more large-capacity generator sets and high-voltage power transmission systems are continuously put into operation, and under the conditions that the system load is continuously increased and the power transmission distance is continuously increased, once the system is disturbed, system oscillation and even fault tripping are easily caused; on the other hand, the harsh geographical environment of the high-voltage transmission line corridor is another important cause of circuit failure. As a first line of defense for power grid safety, the method can quickly, correctly and reliably identify faults and quickly isolate fault elements, and is a basic functional requirement for relay protection. Otherwise, protection malfunction or failure will be caused, and the power supply reliability of the power transmission system is further reduced.

Therefore, the method has important significance for improving the protection reliability and the power supply reliability by quickly and accurately identifying the faults inside and outside the area.

Disclosure of Invention

The invention aims to provide an alternating current transmission line fault identification method based on a multi-fractal spectrum, which can quickly and accurately identify an intra-area fault and an extra-area fault.

The invention is realized by the following technical scheme:

a fault identification method for an alternating current transmission line based on a multi-fractal spectrum comprises the following steps:

s1: when the alternating current transmission system fails, the protection element starts and reads the phase voltage obtained by the high-speed acquisition device at the measuring end, and the voltage fault component of the 5ms time window is obtained according to the superposition principle;

s2: determining the mass distribution probability P of the voltage failure component obtained in step S1_i() By mass distribution probability P_i() Based on the multiple fractal theory, the maximum value α of the singularity index α is calculated_maxAnd minimum value α_min；

S3 maximum value α is used_maxAnd minimum value α_minThe difference value delta α is used for carrying out the inside and outside fault identification, if any one phase or multiple phases of voltage fault components are consistent with delta α > delta α_setIf the three-phase voltage fault components meet the condition that delta α is less than or equal to delta α_setWhen the fault is detected, the fault is judged to be out of range, wherein delta α_setIs the threshold value of the singularity index difference delta α.

The principle of the invention is as follows:

the physical boundary formed by the wave trapper of the alternating-current transmission line has an attenuation effect on the high-frequency component, so that the high-frequency content of the voltage fault component of the measuring end is low when an external fault occurs, the mass distribution probability is relatively uniform in different time periods, and the high-frequency content of the voltage fault component of the measuring end is high when an internal fault occurs, and the mass distribution probability is non-uniform in different time periods. The degree of non-uniformity Δ α of the mass probability distribution is thus used to identify both intra-zone faults and extra-zone faults.

The method calculates the mass distribution probability after obtaining the voltage fault component, and calculates the maximum value α of the singularity index α according to the multi-fractal theory_maxAnd minimum value α_minFinally, the difference delta α between the maximum value and the minimum value is used for carrying out the inside and outside fault identification, if any one phase or multiple phases of voltage fault components meet the conditions that delta α is more than delta α_setIf the three-phase voltage fault components meet the condition that delta α is less than or equal to delta α_setAnd when the fault is judged to be an out-of-area fault, the in-area fault and the out-of-area fault can be quickly and accurately identified.

Further, the expression of the voltage fault component in step S1 is as follows:

u_Mig＝u_Mi-u_Mifg(1)

u in formula (1)_MiThe voltage of the i-phase at the M end in a fault state; u. of_MifgThe voltage of the M terminal i phase in the non-fault state, wherein i is A, B or C.

Further, the mass distribution probability P in step S2_i() The determination process of (2) is as follows:

dividing the voltage fault component into a plurality of small boxes with the same scale along the time direction, and defining the probability density P of mass distribution_i() Comprises the following steps:

in the formula (2), (< 1) represents the size of the small box, n represents the number of boxes, and Δ u represents the number of boxes_i() The difference between the maximum and minimum values for each dimension bin.

Further, the maximum value α of the singularity index α in step S2_maxAnd minimum value α_minThe calculation process of (2) is as follows:

s21: for the mass distribution probability density P_i() Carrying out weighted summation to obtain a distribution function chi_q()：

χ_q()＝∑P_i()^q(3)

In the formula (3), q is a weighting factor;

s22: according to the distribution function χ_q() Finding a generalized dimension D of a multi-fractal spectrum_q：

S23: generalized dimension D from multi-fractal spectra_qAnd weighting q to obtain a quality index τ (q):

τ(q)＝(q-1)D_q(5)

s24: differentiating τ (q) to obtain a singularity index α:

s25: obtaining a multi-fractal spectrum f (alpha) according to the quality index tau (q) and the singularity index alpha:

f(α)＝qα-τ(q) (7)

s26 calculating the maximum α of the singularity index α according to the formula (7)_maxAnd minimum value α_min。

Further, the sampling rate of the phase voltage is taken to be 100kHz in step S1.

Compared with the prior art, the invention has the following advantages and beneficial effects:

1. the invention adopts single-ended voltage data, can reliably and sensitively identify faults without communicating with opposite-end signals, and avoids communication delay.

2. The invention can reliably identify the faults inside and outside the area with different fault initial phase angles, different fault types and different fault distances by utilizing the voltage fault component unevenness, and has better applicability.

3. The data time window of the invention is 5ms, the quick action is better, and the invention has better application prospect.

Drawings

The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:

fig. 1 is a block diagram of a 500kV ac transmission system in accordance with an embodiment of the present invention;

fig. 2 is the degree of unevenness of the a-phase voltage fault component mass distribution probability at the time of the f1 fault;

FIG. 3 shows the degree of nonuniformity of the mass distribution probability of the B-phase voltage fault component when the f1 fault occurs;

fig. 4 is the degree of unevenness of the mass distribution probability of the C-phase voltage fault component at the time of the f1 fault;

fig. 5 is the degree of unevenness of the a-phase voltage failure component mass distribution probability at the time of the f2 failure;

FIG. 6 shows the degree of nonuniformity of the mass distribution probability of the B-phase voltage fault component when the f2 fault occurs;

fig. 7 is the degree of unevenness of the mass distribution probability of the C-phase voltage fault component at the time of the f2 fault;

FIG. 8 is a traversal graph of the maximum value of the three phases Δ α of the non-uniformity degree when the fault occurs in the area and the fault types are AG, AB, ABG, ABC, respectively.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.

Example 1:

a 500kV ac transmission system as shown in fig. 1 was established as a simulation model. The system side of the connecting transformer adopts triangle connection without neutral point, the alternating current line side adopts star connection, and the neutral point is directly grounded. The transmission voltage class of the alternating current line is 500kV, and the transmission line is 300 km.

Fault location: as shown in FIG. 1, f₁And an A-phase grounding fault occurs, the initial phase angle of the fault is 60 degrees, the distance measurement end is 290km, and the sampling frequency is 100 kHz.

S1: when the alternating current transmission system fails, the protection element starts to read phase voltage data u of the measurement point acquired by the high-speed acquisition device at the measurement end_A、u_B、u_CAnd calculateAnd obtaining a voltage fault component in a 5ms time window, wherein the expression is as follows:

u_Mig＝u_Mi-u_Mifg(1)

u in formula (1)_MiThe voltage of the i-phase at the M end in a fault state; u. of_MifgThe voltage of the M terminal i phase in a non-fault state, wherein i is A, B or C;

s2: determining a probability P of a mass distribution of a voltage fault component_i()，

Probability of mass distribution P_i() The determination process of (2) is as follows:

dividing the voltage fault component into a plurality of small boxes with the same scale along the time direction, and defining the probability density P of mass distribution_i() Comprises the following steps:

in the formula (2), (< 1) represents the size of the small box, n represents the number of boxes, and Δ u represents the number of boxes_i() The difference between the maximum value and the minimum value of each dimension small box;

then, the maximum value α of the singularity index α is calculated according to the multi-fractal theory_maxAnd minimum value α_min：

S21: for the mass distribution probability density P_i() Carrying out weighted summation to obtain a distribution function chi_q()：

χ_q()＝∑P_i()^q(3)

In the formula (3), q is a weighting factor;

s22: according to the distribution function χ_q() Finding a generalized dimension D of a multi-fractal spectrum_q：

S23: generalized dimension D from multi-fractal spectra_qAnd weighting q to obtain a quality index τ (q):

τ(q)＝(q-1)D_q(5)

s24: differentiating τ (q) to obtain a singularity index α:

s25: obtaining a multi-fractal spectrum f (alpha) according to the quality index tau (q) and the singularity index alpha:

f(α)＝qα-τ(q) (7)

the minimum value α of the singularity index α of the phase A is calculated by the formula (6) and the formula (7)_min0.2341, singularity index α max α_max1.8830, as shown in FIG. 2, and singularity index α minimum α for phase B_min0.3028, singularity index α max α_max2.2940, as shown in FIG. 3, and singularity index α minimum α for phase C_min0.3027, singularity index α max α_max2.2939, as shown in fig. 4;

s3 maximum value α is used_maxAnd minimum value α_minThe difference Δ α in/out of the area is identified by step S2, in which the degree of unevenness Δ α of phase a is 1.6488, the degree of unevenness Δ α of phase B is 1.9912, and the degree of unevenness Δ α of phase C is 1.9911.

Through simulation, in the system of the example, the threshold value is set to be 1.4, and the unevenness degree delta α of the fault component of the A phase voltage is more than delta α_setF is judged according to the protection criterion₁The fault is an intra-zone fault.

FIG. 8 is a traversal graph of the maximum value of the three phases Δ α of the non-uniformity degree when the fault occurs in the area and the fault types are AG, AB, ABG, ABC, respectively.

Example 2:

a 500kV ac transmission system as shown in fig. 1 was established as a simulation model. The system side of the connecting transformer adopts triangle connection without neutral point, the alternating current line side adopts star connection, and the neutral point is directly grounded. The transmission voltage class of the alternating current line is 500kV, and the transmission line is 300 km.

The type of failure: as shown in FIG. 1, f₂And an AB two-phase ground fault occurs, the initial phase angle is 90 degrees, and the sampling frequency is 100 kHz.

S1: when AC transmission system is out of orderThe protection element starts to read the phase voltage data u of the measuring point acquired by the high-speed acquisition device at the measuring end_A、u_B、u_CAnd calculating to obtain a voltage fault component in a 5ms time window, wherein the expression is as follows:

u_Mig＝u_Mi-u_Mifg(1)

u in formula (1)_MiThe voltage of the i-phase at the M end in a fault state; u. of_MifgThe voltage of the M terminal i phase in a non-fault state, wherein i is A, B or C;

s2: determining a probability P of a mass distribution of a voltage fault component_i() Probability of mass distribution P_i() The determination process of (2) is as follows:

dividing the voltage fault component into a plurality of small boxes with the same scale along the time direction, and defining the probability density P of mass distribution_i() Comprises the following steps:

in the formula (2), (< 1) represents the size of the small box, n represents the number of boxes, and Δ u represents the number of boxes_i() The difference between the maximum value and the minimum value of each dimension small box;

then, the maximum value α of the singularity index α is calculated according to the multi-fractal theory_maxAnd minimum value α_min：

S21: for the mass distribution probability density P_i() Carrying out weighted summation to obtain a distribution function chi_q()：

χ_q()＝∑P_i()^q(3)

In the formula (3), q is a weighting factor;

s22: according to the distribution function χ_q() Finding a generalized dimension D of a multi-fractal spectrum_q：

S23: generalized dimension D from multi-fractal spectra_qAnd weighting q to obtain a quality index τ (q):

τ(q)＝(q-1)D_q(5)

s24: differentiating τ (q) to obtain a singularity index α:

s25: obtaining a multi-fractal spectrum f (alpha) according to the quality index tau (q) and the singularity index alpha:

f(α)＝qα-τ(q) (7)

the minimum value α of the singularity index α of the phase A is calculated by the formula (6) and the formula (7)_min0.6185, maximum value α of singularity index α_max1.4141, as shown in FIG. 5, and singularity index α minimum α for phase B_min0.6258, singularity index α max α_max1.6527, as shown in FIG. 6, and singularity index α minimum α for phase C_min0.6107, singularity index α max α_max1.8186, as shown in fig. 7.

S3 maximum value α is used_maxAnd minimum value α_minThe difference Δ α in/out of the area is identified by step S2, in which the degree of unevenness Δ α of phase a is 0.7956, the degree of unevenness Δ α of phase B is 1.0269, and the degree of unevenness Δ α of phase C is 1.2078.

Through simulation, in the system of the embodiment, the threshold value is set to be 1.4, and the uneven degrees of the three-phase voltage fault components are consistent with that delta α is less than or equal to delta α_setF is judged according to the protection criterion₂The fault is an out-of-range fault.

In summary, the embodiments 1 and 2 of the present invention perform simulation verification on different fault conditions (an intra-area fault and an extra-area fault), and the results show that the present invention can accurately and reliably identify the intra-area fault and the extra-area fault.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (5)

1. A fault identification method for an alternating current transmission line based on a multi-fractal spectrum is characterized by comprising the following steps:

s1: when the alternating current transmission system fails, the protection element starts and reads the phase voltage obtained by the high-speed acquisition device at the measuring end, and the voltage fault component of the 5ms time window is obtained according to the superposition principle;

s2: determining the mass distribution probability P of the voltage failure component obtained in step S1_i() By mass distribution probability P_i() Based on the multiple fractal theory, the maximum value α of the singularity index α is calculated_maxAnd minimum value α_min；

S3 maximum value α is used_maxAnd minimum value α_minThe difference value delta α is used for carrying out the inside and outside fault identification, if any one phase or multiple phases of voltage fault components are consistent with delta α > delta α_setIf the three-phase voltage fault components meet the condition that delta α is less than or equal to delta α_setWhen the fault is detected, the fault is judged to be out of range, wherein delta α_setIs the threshold value of the singularity index difference delta α.

2. The method for identifying the fault of the alternating current transmission line based on the multi-fractal spectrum according to claim 1, wherein the expression of the voltage fault component in the step S1 is as follows:

u_Mig＝u_Mi-u_Mifg(1)

u in formula (1)_MiThe voltage of the i-phase at the M end in a fault state; u. of_MifgThe voltage of the M terminal i phase in the non-fault state, wherein i is A, B or C.

3. The method for identifying the fault of the alternating current transmission line based on the multi-fractal spectrum according to claim 1, wherein the mass distribution probability P in the step S2_i() The determination process of (2) is as follows:

dividing the voltage fault component into a plurality of small boxes with the same scale along the time direction, and defining the mass distributionProbability density P_i() Comprises the following steps:

in the formula (2), (< 1) represents the size of the small box, n represents the number of boxes, and Δ u represents the number of boxes_i() The difference between the maximum and minimum values for each dimension bin.

4. The method for identifying the fault of the alternating current transmission line based on the multi-fractal spectrum according to claim 1, wherein the maximum value α of the singularity index α in the step S2_maxAnd minimum value α_minThe calculation process of (2) is as follows:

s21: for the mass distribution probability density P_i() Carrying out weighted summation to obtain a distribution function chi_q()：

χ_q()＝∑P_i()^q(3)

In the formula (3), q is a weighting factor;

s22: according to the distribution function χ_q() Finding a generalized dimension D of a multi-fractal spectrum_q：

S23: generalized dimension D from multi-fractal spectra_qAnd weighting q to obtain a quality index τ (q):

τ(q)＝(q-1)D_q(5)

s24: differentiating τ (q) to obtain a singularity index α:

s25: obtaining a multi-fractal spectrum f (alpha) according to the quality index tau (q) and the singularity index alpha:

f(α)＝qα-τ(q) (7)

s26 calculating the maximum α of the singularity index α according to the formula (7)_maxAnd minimum value α_min。

5. The method for identifying the fault of the alternating current transmission line based on the multi-fractal spectrum according to any one of claims 1 to 4, wherein the sampling rate of the phase voltage adopted in the step S1 is 100 kHz.

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