 Open Access
 Total Downloads : 835
 Authors : Ankamma Rao J, Bizuayehu Bogale
 Paper ID : IJERTV4IS020429
 Volume & Issue : Volume 04, Issue 02 (February 2015)
 Published (First Online): 21022015
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
Accurate Fault Location Technique on Power Transmission Lines with use of Phasor Measurements
Ankamma Rao J
Bizuayehu Bogale
Assistant Professor Assistant Professor
Electrical& Computer Engineering Dept Electrical & Computer Engineering Dept Samara University, Ethiopia Samara University, Ethiopia
Abstract This paper presents a new approach to fault location on power transmission lines. This approach uses the phasor measurements at one end of the line and benefits from advantages of digital technology and numerical relaying, which are available today and can be applied for offline analysis. This technique uses only end of data and accurate fault distance location is achieved after one cycle from the inception of fault. The analysis for fast identification of fault is evaluated based on the representation of the travelling waves through wavelet modulus maxima. The present criterion can detect the instant of fault, location of fault and kind of fault. MATLAB/ Simulink software was used to test the proposed approach. Various fault conditions were simulated by varying fault type, fault resistance, fault location and fault inception angle, on a given power system model. The simulation results demonstrate the validity of the proposed approach of faulted phase selection.
KeywordsFault location, Current distribution factor, MATLAB, Fault impedance, Fault resistance, Fault inception angle.

INTRODUCTION
Location of faults in power transmission lines is one of main concerns for all electric utilities as the accurate fault location can help to restore the power supply in the shortest possible time. Fault location methods for transmission lines are broadly classified as impedance based method which uses the steady state fundamental components of voltage and current values [13], travelling wave (TW) based method which uses incident and reflected TWs observed at measuring end(s) of the line [4,5], and knowledge based method which uses artificial neural network and/or pattern recognition techniques [6,7]. All the above methods use the measured data either from one end of transmission line or from all ends. The method which uses data from all ends requires synchronized measurement with time stamping and online communication of data to central location [813]. This paper describes a fault location determination method using fault current distribution factors on 400 KV transmission line.

PROPOSED FAULT LOCATION ALGORITHM
Fig.1 Fault network diagram
Fig.2. Incremental positive sequence network diagram
Fig.3.Negative sequence network diagram
d Estimated distance to the fault (units: p.u)
VA_P Protective distance relay voltage at the line end A IA_P Protective distance relay current at the line end A IF Total fault current
ZL Total line impedance
VF Fault voltage
ZA, ZB Source impedances at terminals A and B respectively EA, EB Source voltages at terminals A and B respectively IA1 Incremental positive sequence current.
IA2 Negative sequence current
Z1L Total positive sequence line impedance
Z2L Total negative sequence line impedance
Z1A , Z1B Positive sequence source impedances at terminals A and B respectively
Z2A , Z2B Negative sequence source impedances at terminals A and B respectively.
To derive the Fault location algorithm, the fault loop composed according to the fault classified type is considered. This loop contains the faulted line segment (between points AA and F) and the fault path itself. A generalized model for the fault loop is stated as fallows
(1)
Where
(2)
Fault loop voltages and current can be expressed interns of the local measurements and with using coefficients gathered in Table 1
(3)
(4)
Table1. Coefficients for determining signals defined in Equations (3) and (4)
Voltage drop across the fault path (as shown in the third term in Equation (1)) is expressed using sequence components of total fault current (IF0, IF1, IF2). Determining this voltage drop requires establishing the weighting coefficients. These coefficients can accordingly be determined by taking the boundary conditions for particular fault type. However, there is some freedom for that. Thus, it is proposed firstly to utilize this freedom for avoiding zero sequence quantities. This is well known that the zero sequence impedance of a line is considered as unreliable parameter. This is so due to dependence of this impedance upon the resistivity of a soil, which is changeable and influenced by weather conditions. Moreover, as a result of influence of overhead ground wires, the zero sequence impedance is not constant along the line length. Thus, it is highly desirable to avoid completely the usage of zero sequence quantities when determining the voltage drop across the fault path. This can be accomplished by setting as shown in Table 2, where the alternative sets of the weighting coefficients are gathered. Secondly, the freedom in establishing the weighting coefficients can be utilized for determining the preference for using particular quantities. The negative sequence (Table 2) or the positive sequence (Table 2) can be preferred
For example, considering AG fault one has:
(4)
Thus, symmetrical components of a fault current are:
(5)
It follows from Equation (5) that the total faults current ) can be expressed in the following alternative ways, depending on which symmetrical component is preferred:
(6)
(7)
(8)
(9)
The total fault current (IF) is expressed as weighted sum of its symmetrical components (IF1, IF2, IF0 ) , which can be
determined with use of fault current distribution factors:
(10)
(11)
Multiplying the Equation (17) by the term yields
(12)
Taking into account a set of weighting coefficients that for zero and expressing the symmetrical components of total fault current with use of fault current distribution factors and one obtains:
(13)
Considering that for the fault current distribution factors for positive and negativesequence, with respect to their magnitude and angle, we have
(14)
(15)
The Equation (13) can be rewritten as
(16)
Substitute Equation (16) in the basic Equation (1)
(17)
(18)
Eliminating the term by taking imaginary parts of the
Equation (18) and then rearranging, the resultant formula for the sought distance to fault (d (p.u.) ) is obtained as
(19)
(20)
In formula (19), the angle of the current distribution factor (for the positive or negativesequence) is involved. It is proposed to assume that this angle equals zero ( = 0), i.e., that the fault current distribution factor is a real number. In practice, this assumption is not completely fulfilled and thus there is a certain error due to this.

POWER SYSTEM MODEL
The SimPowerSystem which is an extension to the Simulink of MATLAB software was used to simulate the double end fed power system. The 100 km, 400 kV transmission line was modeled using distributed parameter model as shown in Fig.4
Table:2 Alternative sets of weighting coefficients
REFERENCES
Fig.4 Power System model
The transmission line parameters are as follows: Positive Sequence Resistance, R1 : 0.0275 / km Zero Sequence Resistance, R0 : 0. 275 /km
Zero Sequence Mutual Resistance, R0m : 0.21 /km Positive Sequence Inductance, L1 : 0.00102 H/km Zero Sequence Inductance, L0 : 0.003268 H/km Positive Sequence Capacitance,C1 : 13 e0.009 F/km

SIMULATION RESULTS The fault location error is calculated as

CONCLUSION
(21)

IEEE Guide for Determining Fault Location on AC ransmission and Distribution Lines, IEEE Standard C37.1142004, 2005, pp. 1_36.

S. Lot_fard, M. Kezunovic, and M. J. Mousavi, “A systematic approach for ranking distribution systems fault location algorithms and eliminating false estimates,'' IEEE Trans. Power Del., vol. 28, no. 1, pp. 285_293, Jan.2013.

J. MoraFlÃ²rez, J. MelÃ©ndez, and G. CarrilloCaicedo, `Comparison of impedance based fault location methods for power distribution ystems,'' Electr. Power Syst. Res., vol. 78, no. 4, pp. 657_666, 2008.

Bo ZQ, Johns AT, Aggarwal, AK. A novel fault locator based on the detection of fault generated high frequency transients. In: Proceedings of 6th IEE developments in power systems protection conference; March 1997. p. 197 200.

Evrenosoglu CY, Abur A. Travelling wave based fault location for teed circuits. IEEE Trans Power Deliv 2005;20(2):111521.

Anamika Jain, Kale VS, Thoke AS. Application of artificial neural networks to transmission line faulty phase selection and fault distance location. In: IASTED, Chiang Mai, Thailand; 2931 March 2006. p. 2627.

Fernandez RMC, Rojas HND. An overview of wavelet transforms applications in power systems. In: 14th PSCC, Sevilla, Spain; 2002. p. 18.

L. Eriksson, M. M. Saha, and G. D. Rockefeller, “An accurate fault locator with compensation for apparent reactance in the fault resistance resulting from remoteend infeed,'' IEEE Trans. Power App. Syst., vol. PAS104,no. 2, pp. 423_436, Feb. 1985.

Izykowski J, Rosolowski E, Saha MM (2004) Locating faults in parallel
In this paper, the new accurate algorithm for locating faults on power transmission line with use of the phasor measurements of voltages and currents at one end of the line has been presented. Since numerical relays often store oscillographic and phasor information following the occurrence of a fault, the algorithm can be implemented using information which should be readily available. The complexity of all ten types of faults, fault locations (0100km), fault inception angles (0900), fault resistance (0100 ) are considered. The simulation results show that all ten types of faults are correctly located with fault location error less than 1%.
Fault Type
Fault Resistance
Actual Fault
Location
Estimated Fault
Location
Error (%)
LG
84
18
17.1766
0.8234%
LG
194
36
35.4792
0.5208%
LG
106
54
53.1764
0.8236%
LG
55
75
74.1868
0.8132%
LG
25
86
85.2781
0.7219%
LLG
100
12
12.3849
0.3849%
LLG
166
64
64.2147
0.2147%
LLG
128
48
48.1589
0.1589%
LLG
74
8
8.1988
0.1988%
LL
6
44
44.0529
0.0529%
LL
14
94
95.5680
1.5680%
LLL
2
26
25.3589
0.6411%
LLL
16
56
56.1358
0.1358%
Table 4: Results for all 11 types of faults
transmission lines under availability of complete measurements at one end. IEE Proc Gener Transm Distrib 151(2):268273.

D. Novosel, D. Hart, Y. Hu, and J. Myllymaki, “System for locating faults and estimating fault resistance in distribution networks with tapped loads,'' U.S. Patent 5 839 093, Nov. 17, 1998.

E. O. Schweitzer, III, “Evaluation and development of transmission line faultlocating techniques which use sinusoidal steadystate nformation,'' Comput. Elect. Eng., vol. 10, no. 4, pp. 269_278, 1983.

Distribution Fault Location: Field Data and Analysis, EPRI, Palo Alto,CA, USA, Tech. Rep. 1012438, 2006.

V. NÃºÃ±ez, S. Kulkarni, S. Santoso, and M. Joaquim, “Feature analysis and classi_cation methodology for overhead distribution fault events,'' in Proc.IEEE Power Energy Soc. General Meeting, Jul. 2010, pp. 1_8.

Transmission Line Protection Support Tools: Fault Location Algorithms and the Potential of Using Intelligent Electronic Device Data for Protection Applications, EPRI, Palo Alto, CA, USA, Tech. Rep. 3002002381, 2013.

MATLAB users guide, The Math Works Inc., Natick, MA.