Six Phase Transmission Line Boundary Fault Detection using Mathematical Morphology

Six Phase Transmission Line Boundary Fault Detection using Mathematical Morphology

Kriti Sharma and Shoyab Ali

Department of Electrical Engineering Vedant College of Engineering and Technology

Kota, India sharmakriti0012@gmail.com

Gaurav Kapoor

Department of Electrical Engineering Modi Institute of Technology

Kota, India gaurav.kapoor019@gmail.com

Abstract This paper presents a mathematical morphology based boundary protection scheme for the detection of close-in and remote-end faults that occur on six phase transmission line. A 400 kV, 50 Hz six phase transmission line of 200 km length has been simulated using MATLAB software. The proposed scheme makes use of six phase current measured at the relay location (bus-1) of a six phase transmission line. To assess the performance of the proposed method, various fault parameters are varied. Simulation results reveal the appropriateness of the proposed scheme.

Keywords Six Phase Transmission Line Protection; Mathematical Morphology; Boundary Protection; Fault Detection; Close-In And Remote-End Fault Detection.

1. INTRODUCTION

   For the protection of six phase transmission line against the shunt and series faults, a protection scheme based on logic has been proposed by G. C. Sekhar and P. S. Subramanyam in [1]. A comparative study of electric field calculations beneath six phase and double circuit transmission lines has been described by R. M. Radwn and M. M. Samy in [2]. By the usage of charge simulation technique, calculation of electric field has been done for both double circuit and six phase transmission line at one meter above the earth level. Ebha Koley, Khushaboo Verma and Subhojit Ghosh [3] proposed hybrid WT and modular ANN based scheme for the protection of six phase transmission line which utilized the measured data of single end only. An algorithm for the over current protection of six phase transmission line with the help of numerical relay has been described by Shanker Warathe and R. N. Patel in [4] and based on test results, it was found that the numerical relay protects well six phase transmission line from over current problem. Classification of phase to phase faults on six phase transmission line by using Haar WT and ANN has been reported in [5]. F. Namdari and M. Salehi [6] proposed mathematical morphology and initial current travelling wave based high speed protection scheme for three phase transmission lines. Rapid discrimination of the fault direction and internal faults from the external faults has been done by comparing the arrival time and polarity of the initial current travelling wave captured from both the ends of a transmission

   transmission line protection scheme against lightning strikes. Paulo A. H. Cavalcante et al. [10] proposed a scheme based on simplified multi-resolution morphological gradient (SMMG) for fault location on a three phase transmission line. The proposed scheme is dependent on sampled voltage signals collected from both the ends of a transmission line. Numerous advantages of six phase power transmission line over traditional three phase power transmission lines are: six phase transmission line generates less electric field, less necessity of right of way (ROW) and tower dimensions, increased line inductance and decreased line capacitance, preserved voltage stability, and increased reactive power limit at the far end voltage point [11-14].

   In this paper, a mathematical morphology based fault identification scheme is proposed for the detection of six phase transmission line close-in and remote-end faults. At a variety of fault locations, the performance of scheme is discovered including faults at boundary locations. Distinguish explorations are done to analyze the impact of variation in fault parameters like fault type, fault location, fault resistance, ground resistance, and fault inception angle. Performance of the proposed scheme is tested from 1% of the line length up to 97.5% of the line length. Test results attained by the training of proposed technique validate the suitability of the proposed scheme under a diversity of fault circumstances.

2. SIMULATION OF SIX PHASE TRANSMISSION LINE Test system under consideration is comprised of 400 kV,

   50 Hz, six phase transmission line of length 200 km as demonstrated in Fig.1. The six phase transmission line is connected to a load of 100 MW at the receiving end side. MATLAB software is used for the modeling and simulation of test system for numerous types of faults.

   Six Phase Transmission Line

   Generator

   Relay Load

   line under protection. Ashutosh Kumar Tiwari, Soumya Ranjan Mohanty and Ravindra Kumar Singh [7] proposed

   Bus-1

   Fault

   Bus-2

   mathematical morphology based fault detection technique for the protection of DG penetrated electrical power distribution system. Vinayesh Sulochana, Anish Fransis and Andrew Tickle [8] proposed transmission line fault detection and classification scheme based on morphology and radon processed artificial neural network. Zehui Liang et al. [9] proposed mathematical morphology and integral method based

   Fig.1. Single line diagram of six phase transmission line

3. MATHEMATICAL MORPHOLOGY

   If f (p) is the signal [6] then its domain Df = {x0, x1,xp} and s (q) is the structuring element having domain Dq = {y1,

   y2,…yq} and p > q, where p and q are the integers, then the dilation of f(p) by s (q), denoted by (fs) can be defined as: –

   yd (p) = (fs)(p)=max{f(p-q)+s(q),0(p-q)p,q0}. (1)

   The erosion of f (p) by s (q) denoted as (fs) can be defined as: –

   ye (p) = (fs)(p)=min{f(p+q)-s(q), 0(p+q)p,q0}. (2)

4. PROPOSED FAULT DETECTION SCHEME Fig. 2 depicts proposed fault detection scheme [20].

   Six phase current

   Calculate dilate and erode of six phase current

   Calculate Gradient-1 [Dilate-Erode]

   No fault

   And its Kurtosis (K1) of six phase current

   No fault

   Calculate Gradient-2 [Signal-Erode]

   And its Kurtosis (K2) of six phase current

   No No

   5.1 Phase-AD-g close-in fault

   The proposed scheme is examined for close-in relay phase- AD-g fault occurring at 1% from the relay location with fault inception time of 0.0133 seconds having R f = 10, R g = 15. The six phase current for the period of phase-AD-g fault is shown in Fig. 3. The process of fault detection using mathematical morphological filter during phase- AD-g fault occurring at 1% from bus-1 at FIT = 0.0133 seconds with R f = 10 and R g = 15 can be seen from Fig. 4 to Fig. 5. Fig. 4 to Fig. 5 clarifies the magnitude of gradient-1, 2 and 3 of phase- A and D for the duration of phase-AD-g fault and from Fig. 4 and 5 it is clearly observed that the magnitude of gradients- 1, 2 and 3 of phase-A and D during phase-AD-g fault is higher than the magnitude of gradients-1, 2 and 3 of other phases. Table I summarizes the response of the proposed scheme for phase-AD-g fault occurring at 1% from relay location. As viewed from Table I, the magnitude of gradient-1, 2 and 3 of faulted phase (Phase-A and D) is more than the magnitude of gradient 1, 2 and 3 of un-faulted phase and this explains that the proposed mathematical morphological based fault detector in actual fact detects phase-AD-g fault occurred at 1% from the relay location.

   x 10

   Fault detected

   Fault detected

   Yes Is

   rad-2|faulted phase

   |Grad-2| un-faulted

   Is Yes

   4

   						current(:,1) current(,2) current(:,3) current(:,4) current(:,5) current(:,6)

   1.5

   1

   AD-g

   |Grad-1|faulted phase

   rad-1| un-faultedphase

   > |G

   |G

   Calculate Gradient-3 [Dilate-Signal]

   And its Kurtosis (K3) of six phase current

   >

   phase

   No fault

   Is No

   0.5

   Current (A)

   0

   -0.5

   -1

   -1.5

   0 0.5 1 1.5 2 2.5 3

   |Grad-3|faulted phase >

   Samples

   5

   x 10

   |Grad-3| un-faulted phase

   Fault detected

   Yes

   Fig. 3. Six phase current during phase-AD-g fault at 1% from bus-1 at FIT = 0.0133 seconds with R f = 10 and R g = 15

   Fig. 2. Proposed fault detection scheme

   Gradient-1 (grad1), gradient-2 (grad2) and gradient-3 (grad3) are the three types of mathematical morphological filter coefficients [10]. Following the calculation of these three coefficients, trip decision has been taken. Following six phase fault current decomposition using mathematical morphology filter, if magnitude of gradient-1, 2 or 3 of the faulted phase is

   Grad1

   12000

   10000

   Magnitude

   8000

   6000

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   0

   0 1 2 3

   Grad2

   8000

   7000

   6000

   Magnitude

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   0

   0 1 2 3

   Grad3

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   Magnitude

   5000

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   0

   0 1 2 3

   found larger than the magnitude of gradient-1, 2 or 3 of a healthy phase, the relay detects the fault and issue trip

   Samples

   4

   x 10

   Samples

   4

   x 10

   Samples

   4

   x 10

   command for the tripping of faulty phase (s). For numerous types of faults, the proposed scheme is tested with various

   Fig. 4. Gradients-1, 2, 3 of phase-A during phase-AD-g fault

   fault parameters variation.

5. TEST RESULTS AND DISCUSSIONS

   To scrutinize the performance of mathematical morphological based fault detector, the proposed scheme is tested for various fault cases with variation in fault type, fault location, fault resistance, ground resistance and fault inception time.

   Grad1

   8000

   7000

   6000

   Magnitude

   5000

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   3000

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   1000

   Grad2

   7000

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   Magnitude

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   Grad3

   7000

   6000

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   Magnitude

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   0

   0 1 2 3

   0

   0 1 2 3

   0

   0 1 2 3

   Samples

   4

   x 10

   Samples

   4

   x 10

   Samples

   4

   x 10

   Fig. 5. Gradients-1, 2, 3 of phase-D during phase-AD-g fault

   TABLE I. RELAY OUTPUT FOR PHASE-AD-G FAULT AT 1% FROM BUS-1 AT

   FIT = 0.0133 SECONDS WITH R F = 10 AND R G = 15

   Phase

   Outputs A B C D E F

   10000

   8000

   Magnitude

   6000

   4000

   2000

   Grad1

   6000

   5000

   Magnitude

   4000

   3000

   2000

   1000

   Grad2

   6000

   5000

   Magnitude

   4000

   3000

   2000

   1000

   Grad3

   Dil

   1.2722*

   929.2

   1.0302*

   1.2759*

   865.2

   1.1426*

   0

   0 2000 4000 6000 8000 10000

   Samples

   0

   0 2000 4000 6000 8000 10000

   Samples

   0

   0 2000 4000 6000 8000 10000

   Samples

   Fig. 7. Gradients-1, 2, 3 of phase-A during phase-ABEF-g fault

   8000

   7000

   6000

   Magnitude

   5000

   4000

   3000

   2000

   1000

   Grad1

   5000

   4000

   Magnitude

   3000

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   Grad2

   5000

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   Magnitude

   3000

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   1000

   Grad3

   0

   0 2000 4000 6000 8000 10000

   Samples

   0

   0 2000 4000 6000 8000 10000

   Samples

   0

   0 2000 4000 6000 8000 10000

   Samples

   Fig. 8. Gradients-1, 2, 3 of phase-B during phase-ABEF-g fault

   10^4	827	10^3	10^4	665	10^3
   Erd 1.2712*	853.9	960.7	1.2732*	767.0	1.0743*
   10^4	529	028	10^4	688	10^3
   Grad1 1.1307*	1.5519*	1.4875*	7.7755*	1.4875*	1.3429*
   10^4	10^3	10^3	10^3	10^3	10^3
   7.8811*	1.2593*	1.4458*	6.3013*	1.4448*	1.0005*
   Grad2 10^3	10^3	10^3	10^3	10^3	10^3
   Grad3 7.8811*	1.2593*	1.4458*	6.3013*	1.4448*	1.0005*
   10^3	10^3	10^3	10^3	10^3	10^3

   1. Phase-ABEF-g remote-end fault

      The proposed scheme is tested for remote-end phase- ABEF-g low resistance fault occurring at 95% from the relay location with fault inception time of 0.02833 seconds having R f = 0.5, R g = 1. The six phase current for the duration of phase-ABEF-g fault is shown in Fig. 6. The process of fault detection using mathematical morphological filter during phase- ABEF-g fault occurring at 95% from bus-1 at FIT =

      10000

      8000

      Magnitude

      6000

      4000

      2000

      0

      Grad1

      0 2000 4000 6000 8000 10000

      Samples

      7000

      6000

      5000

      Magnitude

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      0

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      Samples

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      6000

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      Magnitude

      4000

      3000

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      1000

      0

      Grad3

      0 2000 4000 6000 8000 10000

      Samples

      0.02833 seconds with R f = 0.5 and R g = 1 can be seen from Fig. 7 to Fig. 10. Fig. 7 to Fig. 10 describes the

      Fig. 9. Gradients-1, 2, 3 of phase-E during phase-ABEF-g fault

      magnitude of gradient-1, 2 and 3 of six phases for the duration of phase-ABEF-g fault and from Fig. 7 to Fig. 10 it is clearly observed that the magnitude of gradients-1, 2 and 3 of phase- A, B, E and F during phase-ABEF-g fault is higher than the magnitude of gradients-1, 2 and 3 of other phases. Table II highlights the response of the proposed scheme for phase- ABEF-g fault occurring at 95% from relay location. As viewed from Table II, the magnitude of gradient-1, 2 and 3 of faulted phase is higher than the magnitude of gradient 1, 2 and

      Grad1

      9000

      8000

      7000

      Magnitude

      6000

      5000

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      0

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      Samples

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      Samples

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      Magnitude

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      0 2000 40006000 8000 10000

      Samples

      3 of un-faulted phase and this explains that the proposed mathematical morphological based fault detector in point of fact detects phase-ABEF-g fault occurred at 95% from the relay location which is mainly a remote-end low resistance fault.

      Fig. 10. Gradients-1, 2, 3 of phase-F during phase-ABEF-g fault

      TABLE II. RELAY OUTPUT FOR PHASE-ABEF-G FAULT AT 95% FROM BUS-1

      		Phase
      Outputs A	B	C	D	E	F
      Dil 3.1552*	7.8973*	1.5010*	1.2483*	4.5779*	6.6614*
      10^3	10^3	10^3	10^3	10^3	10^3
      Erd 3.0995*	7.7891*	969.8	966.1	4.3562*	5.9316*
      10^3	10^3	007	331	10^3	10^3
      Grad1 9.5591*	7.7628*	2.3589*	1.9644*	9.7774*	8.4613*
      10^3	10^3	10^3	10^3	10^3	10^3
      Grad2 5.5240*	4.7516*	1.8681*	1.3764*	6.5126*	5.7584*
      10^3	10^3	10^3	10^3	10^3	10^3
      Grad3 5.5240*	4.7516*	1.8681*	1.3764*	6.5126*	5.7584*
      10^3	10^3	10^3	10^3	10^3	10^3

      AT FIT = 0.02833 SECONDS WITH R F = 0.5 AND R G = 1

      8000

      6000

      4000

      Current (A)

      2000

      0

      -2000

      -4000

      -6000

      ABEF-g

      						current(:,1) current(:,2) current(:,3) current(:,4) current(:,5) current(:,6)

      -8000

      -10000

      0 0.5 1 1.5 2 2.5 3

      Samples

      4

      x 10

      Fig. 6. Six phase current during phase ABEF-g fault at 95% from bus-1 at FIT = 0.02833 seconds with R f = 0.5 and R g = 1

   2. Phase-ABCDEF-g remote-end fault

   The proposed scheme is examined for remote-end phase- ABCDEF-g low resistance fault occurring at 85% from the relay location with fault inception time of 0.03166 seconds having R f = 10, R g = 15. The six phase current for the period of phase-ABCDEF-g fault is shown in Fig. 11. The procedure of fault detection using mathematical morphological filter for the period of phase- ABCDEF-g fault happening at

   85% from bus-1 at FIT = 0.03166 seconds with R f = 10 and

   Grad1

   14000

   12000

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   Magnitude

   Magnitude

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   Samples

   Grad2

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   R g = 15 can be seen from Fig. 12 to Fig. 17. Fig. 12 to Fig.

   Fig. 14. Gradients-1, 2, 3 of phase-C during phase-ABCDEF-g fault

   17 illustrates the magnitude of gradient-1, 2 and 3 of six phases for the period of phase-ABCDEF-g fault and from Fig. 12 to Fig. 17 it is noticeably observed that the magnitude of gradients-1, 2 and 3 of all six phases during phase- ABCDEF-g fault increases. Table III summarizes the response of the proposed scheme for phase-ABCDEF-g fault occurring at 85% from relay location. As inspected from Table

   12000

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   III, the magnitude of gradient-1, 2 and 3 of all six faulted phase raises and this clarifies that the proposed mathematical

   0

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   0

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   Samples

   0

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   Samples

   morphological based fault detector in point of fact detects

   Fig. 15. Gradients-1, 2, 3 of phase-D during phase-ABCDEF-g fault

   phase-ABCDEF-g fault occurred at 85% from the relay location which is essentially a remote-end low resistance fault.

   14000

   12000

   Grad1

   14000

   12000

   Grad2

   14000

   12000

   Grad3

   4

   x 10

   						current(:,1) current(:,2) current(:,3) current(:,4) current(:,5) current(:,6)

   1

   ABCDEF-g

   10000

   Magnitude

   8000

   10000

   Magnitude

   8000

   10000

   Magnitude

   8000

   0.5

   6000

   4000

   6000

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   4000

   Current (A)

   2000

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   0

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   Samples

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   Samples

   2000

   0

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   Samples

   -0.5

   Fig. 16. Gradients-1, 2, 3 of phase-E during phase-ABCDEF-g fault

   -1

   0 0.5 1 1.5 2 2.5 3

   14000

   Grad1

   14000

   Grad2

   14000

   Grad3

   Samples

   4

   x 10

   12000

   12000

   12000

   Fig. 11. Six phase current during phase ABCDEF-g fault at 85% from bus-1 at FIT = 0.03166 seconds with R f = 10 and R g = 15

   10000

   Magnitude

   8000

   10000

   Magnitude

   8000

   10000

   Magnitude

   8000

   14000

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   Magnitude

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   nitude

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   nitude

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   6000	6000	Mag	6000	Mag
   4000	4000		4000
   2000 0	2000 0		2000 0/p>		TABLE III. RELAY OUTPUT FOR PHASE-ABCDEF-G FAULT AT 85% FROM BUS-1 AT FIT = 0.03166 SECONDS WITH R F = 10 AND R G = 15

   Fig. 17. Gradients-1, 2, 3 of phase-F during phase-ABCDEF-g fault

   0 500 1000 1500 2000 2500

   Samples

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   Samples

   		Phase
   Outputs A	B	C	D	E	F
   5.4351*	5.7897*	8.1342*	6.0585*	5.4672*	8.3995*
   Dil 10^3	10^3	10^3	10^3	10^3	10^3
   5.0707*	5.3053*	7.5893*	5.4177*	5.0268*	7.9739*
   Erd 10^3	10^3	10^3	10^3	10^3	10^3
   Grad1 1.2881*	1.1848*	1.2776*	1.1848*	1.2776*	1.2881*
   10^4	10^4	10^4	10^4	10^4	10^4
   Grad2 1.2881*	1.1743*	1.2776*	1.1743*	1.2776*	1.2881*
   10^4	10^4	10^4	10^4	10^4	10^4
   Grad3 1.2881*	1.1743*	1.2776*	1.1743*	1.2776*	1.2881*
   10^4	10^4	10^4	10^4	10^4	10^4

   Fig. 12. Gradients-1, 2, 3 of phase-A during phase-ABCDEF-g fault

   12000

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   Fig. 13. Gradients-1, 2, 3 of phase-B during phase-ABCDEF-g fault

6. CONCLUSION

In this paper, a mathematical morphology based boundary protection scheme is proposed for six phase transmission line. The proposed scheme exploits dilation and erosion coefficients of six phase fault current measured at the relay location (Bus- 1). The proposed scheme effectively detects both close-in and remote-end faults that occur on six phase transmission line. The proposed scheme is tested for numerous categories of boundary faults with fault parameters variation. Simulation results show that both close-in and remote-end faults are correctly detected by mathematical morphology based fault detection scheme.

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