A. M. Sharaf, Senior Member, IEEE University of New Brunswick, Fredericton, NB, Canada
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Transcript of A. M. Sharaf, Senior Member, IEEE University of New Brunswick, Fredericton, NB, Canada
A New Current Pattern Recognizing Protection
Technique for High Impedance Fault Using Cross Correlation
A. M. Sharaf, Senior Member, IEEE
University of New Brunswick,
Fredericton, NB, Canada
M. M. Eissa, Senior Member, IEEE
Faculty of Engineering, Helwan University,
EGYPT
High Impedance Arc-Type Faults (HIF) on Meshed Electrical Distribution/Utilization networks are characterized by an intermittent Arc-type nature and low-level of the fault currents.
Problem to be solve
In the multi-grounded distribution line, there exists unbalance in three phase loads, therefore, overcurrent ground relays are usually set high to allow some large neutral currents due to this unbalance.
The detection of low-level ground-currents using any conventional over-current or ground fault type relays is both difficult and sometimes inaccurate.
Each detection method may increase the possibility of the detection for high impedance faults to some extent, but it also has some drawbacks as well. Until now, no technique has offered a complete solution for this problem.
The paper presents the application of the cross correlation technique as a pattern recognition to high impedance faults (HIFs). The third and fifth harmonics current components are extracted from the fault current using Fast Fourier Transform (FFT).
Aim of the paper
Correlation is a measure of the relation between two or more variables. The measurement scales used should be at least interval scales, but other correlation coefficients are available to handle other types of data.
CROSS CORRELATION AS PATTERN CLASSIFICATION
Following the definition of the cross correlation function between x[n] and y[n] given by (1).
where k is a delay units.
(1)
The cross correlation functions of power signals are redefined such that the summations and integrations are replaced by averages. For two discrete power signals x[n] and y[n] the cross correlation function is defined as (2):
This feature of pattern classification is used in this paper.
(2)
The technique is based on a novel low frequency (the third and fifth harmonic feature diagnostic vector).
OVERALL PROCEDURE OF THE TECHNIQUE
The instantaneous current values at feeder substation buses shown in Fig. 1 are captured and transformed into frequency domain using one cycle Fast Fourier Transform FFT.
The FFT harmonic vectors extraction [i3] and [i5] are processed to obtain feature vectors.
The current pattern is classified using the cross correlation function given in (2).
S R
R1
F2 F1
X km
FFT
Pattern Classification
Fault Vector Feature
HIF with Linear or
Non-linear ARC
The slop of the Cross Correlation Function “XCF“ can be calculate to discriminate between linear and non-linear arc conditions
Threshold
• If the slop of “XCF“ goes lower than some THR_SLOP value, the technique will identify that the fault is linear HIF
• If the slop of “XCF“ goes higher than a THR_SLOP value, HIF is identified as a non-linear arc fault
The system includes a 138 kV. X is taken in per unit length. Data for verifying the proposed technique was generated by modeling the selected system using the Matlab/Simulink model
SYSTEM
The model
ic1v1
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den(s)
x lineiF
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i23
i1
v1
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i5
i3
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v2
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p2Source B
Source A
Scope
1
7e-3s+0.7
Rs Ls1
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7e-3s+0.7
Rs Ls
In1Out1
NLL Linear/NL
In1Out1
LN
1s
1s
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v2
i2
p2
v3v5i3i5
p3p5
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i1
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FT
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1/(c*x)
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1/(c*(l-x))
1
den(s)
(1-x) line
is1
i1
i2
The performance of the proposed technique has been evaluated for different types of internal faults. A wide variation of fault locations, source impedances, close in fault and fault resistances were investigated.
TEST RESULTS
Performance of the relay for a phase-a-to ground fault on the transmission line is shown in the following figure
The fault is located at 30% of transmission line length from R1
Effect of Internal Linear Fault
The corresponding computed “XCF“ for R1 has positive value. For the selected threshold boundary THR_SLOP, the “XCF“ slop is lower than this boundary. This indicates that the fault is a linear fault.
The computed [i3] and [i5] pattern is shown in Figure. The corresponding computed “XCF“ for R1 has very rise value 1.6E-02. For the selected threshold boundary, the “XCF“ does cross the selected threshold boundary
Effect of Internal Non-Linear Fault
The paper introduced a novel low order harmonic current pattern for HIGH IMPEDANCE FAULT ARC detection and discrimination.
CONCLUSIONS
The technique is based on analyzing the current pattern shape.
The suggested technique was tested under different fault conditions.
The paper introduced a novel low order harmonic current pattern for HIGH IMPEDANCE FAULT ARC detection and discrimination.
The great selectivity and reliability are the main features in discrimination between linear and non-linear arc faults.