Detection and Location of Faults in 11KV Underground Cable by using Continuous Wavelet Transform (CWT)
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This document presents a technique for detecting, classifying, and locating faults on an 11kV underground cable system using continuous wavelet transform (CWT). Faults generate high frequency signals that propagate along the cable. CWT is applied to extract these signals and analyze them to determine the fault location based on the travel time of the signals. A 100km long cable is modeled in MATLAB and faults are simulated at different locations. CWT effectively extracts the high frequency components from the fault signals. The results show that CWT can accurately detect and locate faults by analyzing the extracted signal components. Fault location is determined by measuring the time difference between peaks in the CWT coefficients.
![IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE)
e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 10, Issue 1 Ver. IV (Jan – Feb. 2015), PP 44-50
www.iosrjournals.org
DOI: 10.9790/1676-10144450 www.iosrjournals.org 44 | Page
Detection and Location of Faults in 11KV Underground Cable by
using Continuous Wavelet Transform (CWT)
D. Prabhavathi1
, K.Prakasam2
, Dr.M.Suryakalavathi3
, B.Ravindranath Reddy4
1,2
Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, INDIA
3,4
Jawaharlal Nehru Technological University, Kukatpally, Hyderabad, Andhra Pradesh, INDIA
Abstract: This paper describes a technique to detect, classify and locate faults on an underground cable system
based on the principles of continuous wavelet transform (CWT). Due to the fault in the power system a high
frequency current and voltage generates and propagate along the power. These generated signals contain a lot
of information and can be used for fault detection and location. The high frequency components generated are
extracted using the wavelet technique and analysis of the extracted signals is carried. The MATLAB simulink
version 7.6 is used to model the underground cable network and faults at various locations are simulated. The
resulting waveforms are subjected through a wavelet transform to extract the required signals for analysis. The
results show that the wavelet transform is very effective to extract the transient components from the fault
signals and detection and location of faults can be done accurately. In this paper three phase 11KV; 100km long
cable is considered for the analysis purpose.
Keywords: Cable, CWT, fault location, transient, signals, simulation
I. Introduction
In the modern electrical power systems of transmission and distribution systems, underground cable is
used largely in urban areas and compared to overhead lines, fewer faults occur in underground cables. However
if faults occur, it’s difficult to repair and locate the fault. Faults that could occur on underground cables
networks are single phase-to-earth (LG) fault; double phase-to-earth (LLG) fault, phase-to-phase (LL) fault and
three phase-to-earths (LLLG) fault [1]. The single line to earth fault is the most common fault type and occurs
most frequently. Fault detection and location based on the fault induced current or voltage travelling waves has
been studied for years together. In all these techniques, the location of the fault is determined using the high
frequency transients. The main idea behind these techniques is based on the reverberation of the fault generated
travelling waves in the faulty system. Fault location based on the travelling waves can generally be categorized
into two: single-ended and double ended. For single-ended, the current or voltage signals are measured at one
end of the line and fault location relies on the analysis of these signals to detect the reflections that occur
between the measuring point and the fault. For the double-ended method, the time of arrival of the first fault
generated signals are measured at both ends of the lines using synchronized timers. The double-ended method
does not require multiple reflections of the signals. However, single-ended location is preferred as it only
requires one unit per line and a communication link is not necessary.
This paper presents a wavelet technique have been applied that can extract the high frequency fault
signals for determination of cable fault and location. The technique applied here determines the fault position by
measuring the travelling time of the high frequency current signals. In this paper 11kV distribution cable is
modeled using MATLAB Simulink software, the response for the different fault was examined and then wavelet
transform is applied with band pass filter to derive the exact location of the fault.
II. Wavelet Transform
Wavelet transform is much like the Fourier transforms, however with one important difference: it
allows time localization of different frequency components of a given signal. Windowed Fourier transform also
partially achieves this same goal, but with a limitation of using a fixed width windowing function. In the case of
wavelet transform, the analyzing functions, which are called wavelets, will adjust their time widths to their
frequency in such a way that, higher frequency wavelet will be narrow and lower frequency ones will be
broader. So this property of multi resolution is particularly useful for analyzing fault transients which contain
localized high frequency components superposed on power frequency signals. Thus, wavelet transform is better
suited for analysis of signals containing short lived high frequency disturbances superposed on lower frequency
continuous waveform by virtual of this zoom in capability [2]. Given a function ƒ (t), its continuous wavelet
transform (WT) will be calculated as follows:
(1)](https://image.slidesharecdn.com/g010144450-151119104042-lva1-app6892/85/Detection-and-Location-of-Faults-in-11KV-Underground-Cable-by-using-Continuous-Wavelet-Transform-CWT-1-320.jpg)
![Detection And Location Of Faults In 11kv Underground Cable Using Continuous Wavelet…
DOI: 10.9790/1676-10144450 www.iosrjournals.org 49 | Page
Table-1
LG Fault
Actual
Distance(km)
Calculated
Distance(km)
% Error
25 24.81 0.38
50 50.12 -0.24
Table-2
LLG Fault
Actual
Distance(km)
Calculated
Distance(km)
%
Error
25 24.37 1.26
50 54.26 8.52
Table-3
IV. Conclusions
Detection and location of faults are very important in the power system as they are the basic of
protection of the power system. If detection and location of faults are not accurate the protective devices can not
trip properly and required operation cannot be done, which may leads to damage of the large equipments. In this
paper 11kv 50km long under ground cable was modeled using Mat lab simulink and simulation was carried at
different fault points of 25km and 50 km with the fault resistance of 1Ω and continuous wavelet transform
technique is applied to extract the transient current. The results are obtained with the sampling rate of 8000 Hz
with a wavelet transform of Daubechies Db4.For the sampling period of 0.00125,For scale a of 11.4285 the
output waveform will have a frequency of 50Hz. Fig 2, 4 and 6 shows phase currents of single line to earth fault
(AG), double line to earth fault (ABG) and triple line to earth fault (ABCG) at 25 km with fault resistance of
1Ω.Fig 3,5and 7 shows the transient current extracted using the continuous wavelet transform for 25km with a
fault resistance of 1Ω. Fig 8, 10 and 12 shows phase currents of single line to earth fault (AG), double line to
earth fault (ABG) and triple line to earth fault (ABCG) at 50 km with fault resistance of 1ohm.Fig 9,11and 13
shows the transient current extracted using the continuous wavelet transform for 50 km with a fault resistance of
1Ω. The location of fault can be calculated from the equation (2), in the calculation of fault location 10μs
sampling time is used , the difference between the transient signal arrival of first fault signal and arrival of the
reflected fault signal is multiplied by 10μs.The velocity of travelling time in the cable as 1.9557x105
km/s,the
distance to the fault from the calculated pint are tabulated in the Tables-1,Table-2 and Table-3.
Acknowledgements
The authors wish to gratefully acknowledge technical support for this research work by Smt. Dr. M.
Suryakalavathi .Dept of E.E.E, J.N.T.U.HHyderbad , and her support for the completion of this work. and
gratefully acknowledge to Dr.B.Ravindranath Reddy for his valuable suggestions in completions of this work
Mr.G.Prashuram, Angel technology, Hyderabad for the provided support Last but not least the author thank the
management of Sri Sivani College of Engineering for their great and continuous support for the completion of
the research work
References
[1]. Kuan, K.K & Warwick, K. (1992) Real-Time Expert System for Fault Location on High Voltage Underground Distribution Cables.
IEE Publications Proceedings-c, Vol. 139, No.3, pp. 235-240.
[2]. Crossley P.A. and MacLaren P.G. (1983) Distance protection based on travelling waves. IEEE Transactions on Power Apparatus
and System. Vol. PAS 102, No.9, September: 2971-2983.
[3]. Ancell G.B. & Pahalawaththa N.C. (1994) Maximum likelihood estimation of fault location on transmission lines using travelling
waves. IEEE Transactions on Power Delivery. Vol. 9, No. 2, April: 680-689.
[4]. Jie Liang, Elangovan S., Devotta J.B.X. (1999) Adaptive travelling wave protection algorithm using two correlation functions.
IEEE Transactions on Power Delivery. Vol. 14, No.1, January: 126-131.
[5]. Bo Z.Q., Weller G., Redfern M.A. (1999) Accurate fault location technique for distribution system using fault-generated high-
frequency transient voltage signals. IEE Proceedings - Generation, Transmission and Distribution. Volume 146, Issue 1, January: 73
– 79.
[6]. Crossley P.A., Gale P.F, Aurangzeb M. (2001) Fault location using high frequency travelling waves measured at a single location
on a transmission line. Developments in Power System Protection. Amsterdam, Holland, 9-12 April: 403-406.
[7]. Elhaffar, A. and Lehtonen, M. (2004) Travelling waves based earth fault location in 400 kV transmission network using single end
measurement. Large Engineering Systems Conference on Power Engineering. LESCOPE-04., 28-30 July: 53 – 56.](https://image.slidesharecdn.com/g010144450-151119104042-lva1-app6892/85/Detection-and-Location-of-Faults-in-11KV-Underground-Cable-by-using-Continuous-Wavelet-Transform-CWT-6-320.jpg)
![Detection And Location Of Faults In 11kv Underground Cable Using Continuous Wavelet…
DOI: 10.9790/1676-10144450 www.iosrjournals.org 50 | Page
[8]. Thomas, D.W.P., Christopoulos, C., Tang, Y., Gale, P., Stokoe, J. (2004) Single ended travelling wave fault location scheme based
on wavelet analysis. Eighth IEE International Conference on Developments in Power System Protection, Volume 1, 5-8 April: 196 -
199.
[9]. Zeng Xiangjun, Li, K.K., Liu Zhengyi, Yin Xianggen (2004) Fault location using traveling wave for power networks. Industry
Applications Conference. 39th IAS Annual Meeting, 3-7 Oct.: 2426 - 2429. International Journal of Engineering and Technology,
Vol. 6, No.2, 2009, pp. 90-95 ISSN 1823-1039 2009 FEIIC 95
[10]. Evrenosoglu, C.Y. and Abur, A. (2005) Travelling wave based fault location for teed circuits. IEEE Transactions on Power
Delivery. Volume 20, Issue 2, Part 1, April: 1115 – 1121.
[11]. Fernando H.M and Ali.A (1998) Fault Location using Wavelet. IEEE Transaction on Power Delivery, Vol.13, No
Biographies Of Author
D. Prabhavathi Born in 1976 august 27, her B.Tech degree from KSRM college of Engineering, kadapa , SV
university, and M.Tech degree from SV university in the year 2003.She has specialized in
Power Systems, High Voltage Engineering. She is currently working as Prof & HOD , Dept
of EEE Sri Sivani Institute of Technology srikakulam, A.P. INDIA. Her research interests
include Simulation studies on faults identification in UG cable of LT and HT, Fuzzy logic,
High Voltage Engineering, Power Electronics and drives modeling and design for reactive
power compensations etc she has 13 years of experience.
K .Prakasam, Born in 1973 April 20, his B.Tech degree from K.S.R.M College of Engineering S.V University
in 1997 and M.Tech degree from S.V University in the year 2004. He has specialized in Power
Systems, High Voltage Engineering and Control Systems. His research interests include
Simulation studies on very fast Transients of different power system equipment, Power quality,
Fuzzy logic, Power Electronics and drives control, He has 16 years of experience. He is
presently working as Prof and HOD of Dept of EEE, and Academic Director of Sri Sivani
College of Engineering Srikakulam, A.P, INDIA.
Dr. M. Surya Kalavathi, Born on 8th July 1966, Obtained her B.Tech degree from S.V. U. in 1988 and
M.Tech from S.V.U. in the year 1992. Obtained her doctoral degree from JNTU, Hyderabad
and Post Doctoral from CMU, USA. She is presently the Professor (EEE) in JNTUH College of
Engineering, Kukatpally, Hyderabad. Published 16 Research Papers and presently guiding 5
Ph.D. Scholars. She has specialized in Power Systems, High Voltage Engineering and Control
Systems. Her research interests include Simulation studies on Transients of different power
system equipment. She has 18 years of experience. She has invited for various lectures in
institutes.
Bhumanapally. Ravindhranath Reddy, Born on 3rd September, 1969. Got his B.Tech in Electrical &
Electronics Engineering from the J.N.T.U.A, College of Engg., Anantapur in the year 1991s
Completed his M.Tech in Energy Systems in IPGSR of J.N.T.University Hyderabad in the year
1997. Obtained his doctoral degree from JNTU,Hyderabad. He is presently guiding PhD
scholars.](https://image.slidesharecdn.com/g010144450-151119104042-lva1-app6892/85/Detection-and-Location-of-Faults-in-11KV-Underground-Cable-by-using-Continuous-Wavelet-Transform-CWT-7-320.jpg)
Detection and Location of Faults in 11KV Underground Cable by using Continuous Wavelet Transform (CWT)
- 1. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 10, Issue 1 Ver. IV (Jan – Feb. 2015), PP 44-50 www.iosrjournals.org DOI: 10.9790/1676-10144450 www.iosrjournals.org 44 | Page Detection and Location of Faults in 11KV Underground Cable by using Continuous Wavelet Transform (CWT) D. Prabhavathi1 , K.Prakasam2 , Dr.M.Suryakalavathi3 , B.Ravindranath Reddy4 1,2 Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, INDIA 3,4 Jawaharlal Nehru Technological University, Kukatpally, Hyderabad, Andhra Pradesh, INDIA Abstract: This paper describes a technique to detect, classify and locate faults on an underground cable system based on the principles of continuous wavelet transform (CWT). Due to the fault in the power system a high frequency current and voltage generates and propagate along the power. These generated signals contain a lot of information and can be used for fault detection and location. The high frequency components generated are extracted using the wavelet technique and analysis of the extracted signals is carried. The MATLAB simulink version 7.6 is used to model the underground cable network and faults at various locations are simulated. The resulting waveforms are subjected through a wavelet transform to extract the required signals for analysis. The results show that the wavelet transform is very effective to extract the transient components from the fault signals and detection and location of faults can be done accurately. In this paper three phase 11KV; 100km long cable is considered for the analysis purpose. Keywords: Cable, CWT, fault location, transient, signals, simulation I. Introduction In the modern electrical power systems of transmission and distribution systems, underground cable is used largely in urban areas and compared to overhead lines, fewer faults occur in underground cables. However if faults occur, it’s difficult to repair and locate the fault. Faults that could occur on underground cables networks are single phase-to-earth (LG) fault; double phase-to-earth (LLG) fault, phase-to-phase (LL) fault and three phase-to-earths (LLLG) fault [1]. The single line to earth fault is the most common fault type and occurs most frequently. Fault detection and location based on the fault induced current or voltage travelling waves has been studied for years together. In all these techniques, the location of the fault is determined using the high frequency transients. The main idea behind these techniques is based on the reverberation of the fault generated travelling waves in the faulty system. Fault location based on the travelling waves can generally be categorized into two: single-ended and double ended. For single-ended, the current or voltage signals are measured at one end of the line and fault location relies on the analysis of these signals to detect the reflections that occur between the measuring point and the fault. For the double-ended method, the time of arrival of the first fault generated signals are measured at both ends of the lines using synchronized timers. The double-ended method does not require multiple reflections of the signals. However, single-ended location is preferred as it only requires one unit per line and a communication link is not necessary. This paper presents a wavelet technique have been applied that can extract the high frequency fault signals for determination of cable fault and location. The technique applied here determines the fault position by measuring the travelling time of the high frequency current signals. In this paper 11kV distribution cable is modeled using MATLAB Simulink software, the response for the different fault was examined and then wavelet transform is applied with band pass filter to derive the exact location of the fault. II. Wavelet Transform Wavelet transform is much like the Fourier transforms, however with one important difference: it allows time localization of different frequency components of a given signal. Windowed Fourier transform also partially achieves this same goal, but with a limitation of using a fixed width windowing function. In the case of wavelet transform, the analyzing functions, which are called wavelets, will adjust their time widths to their frequency in such a way that, higher frequency wavelet will be narrow and lower frequency ones will be broader. So this property of multi resolution is particularly useful for analyzing fault transients which contain localized high frequency components superposed on power frequency signals. Thus, wavelet transform is better suited for analysis of signals containing short lived high frequency disturbances superposed on lower frequency continuous waveform by virtual of this zoom in capability [2]. Given a function ƒ (t), its continuous wavelet transform (WT) will be calculated as follows: (1)
- 2. Detection And Location Of Faults In 11kv Underground Cable Using Continuous Wavelet… DOI: 10.9790/1676-10144450 www.iosrjournals.org 45 | Page Where, a and b are the scaling (dilation) and translation (time shift) constants respectively, and ψ is the wavelet function (mother wavelet). The continuous wavelet transform (CWT) computes the inner product of a signal (t), with translated and dilated versions of an analyzing wavelet, (t) the definition of the CWT is: C = You can also interpret the CWT as a frequency-based filtering of the signal by rewriting the CWT as an inverse Fourier transform. C = d Where f( and are the Fourier transforms of the signal and the wavelet. From the preceding equations, you can see that stretching a wavelet in time causes its support in the frequency domain to shrink. In addition to shrinking the frequency support, the center frequency of the wavelet shifts towards lower frequencies. This depicts the CWT as a band pass filtering of the input signal. CWT coefficients at lower scales represent energy in the input signal at higher frequencies, while CWT coefficients at higher scales represent energy in the input signal at lower frequencies. However, unlike Fourier band pass filtering, the width of the band pass filter in the CWT is inversely proportional to scale. The width of the CWT filters decreases with increasing scale. This follows from the uncertainty relationships between the time and frequency support of a signal: the broader the support of a signal in time, the narrower its support in frequency. The converse relationship also holds. In the wavelet transform, the scale or dilation operation is defined to preserve energy. To preserve energy while shrinking the frequency support requires that the peak energy level increases. The quality factor or Q factor of a filter is the ratio of its peak energy to bandwidth. Because shrinking or stretching the frequency support of a wavelet results in commensurate increases or decreases in its peak energy, wavelets are often referred to as constant-Q filters. III. Fault Detection And Location By comparing the transient signals at all phases the classification of fault can be made .If the transient signal appears at only one phase then the fault is single line to ground fault The transient signals generated by the fault is no stationary and is of wide band of frequency, when fault occurs in the network, the generated transient signals travels in the network. On the arrival at a discontinuity position, the transient wave will be partly reflected and the remainder is incident to the line impedance. The transient reflected from the end of the line travels back to the fault point where another reflection and incident occur due to the discontinuity of impedance. To capture these transient signals wavelet analysis can be used. The fault location can be carried out by comparing the aerial mode wavelet coefficient to determine the time instant when the energy of the signal reaches its peak value. The distance between the fault point and the bus of the faulted branch will be given by D = (2) Where D is the distance to the fault, td is the time difference between two consecutive peaks of the wavelet transform coefficients of the recorded current and v is the wave propagation velocity of the aerial mode. A. Modeling and Simulation: First 11 KV, 100km underground cable is modeled in MATLAB simulink with 7.6 version and response of the complete system is for different configuration and faults evaluated. Wavelet transform effectively acts as a band pass filter which extracts a band of high frequency transient current signals from the faulted cable. The total length of the cable considered is 100km. Results from simulations are obtained with 800 Hz sampling rate and with Wavelet transform of Daubechies Db-4. The travelling wave velocity of the signals in the 11kV underground cable system is 1.9557x105 km/s, and sampling time of 10μs is used. Fig 1 depicts the single line diagram of the simulated system which is 11kv, 50Hz, 50km under ground cable.
- 3. Detection And Location Of Faults In 11kv Underground Cable Using Continuous Wavelet… DOI: 10.9790/1676-10144450 www.iosrjournals.org 46 | Page Simulation studies: In this paper the authors select all the possible cases to illustrate the performance of the proposed technique under fault conditions. First LG fault is selected as simulation case and fault locations are tabulated along with % error to compare the deviation from the actual values using continuous wavelet transform. Similarly for simulation and their results are tabulated. LLG and LLLG faults selected 0 500 1000 1500 2000 2500 3000 3500 4000 4500 -1000 -500 0 500 1000 1500 ia ib ic Fig 2: phase current for LG (AG)fault at 25 km Fig 3: Single line to earth fault (AG) at 25km 0 500 1000 1500 2000 2500 3000 3500 4000 4500 -2000 -1500 -1000 -500 0 500 1000 1500 2000 ia ib ic Fig 4: Phase current for LLG fault (ABG) at 25km Fig 5: Double line to earth fault (ABG) at 25km by wavelet transforms
- 4. Detection And Location Of Faults In 11kv Underground Cable Using Continuous Wavelet… DOI: 10.9790/1676-10144450 www.iosrjournals.org 47 | Page 0 500 1000 1500 2000 2500 3000 3500 4000 4500 -2000 -1500 -1000 -500 0 500 1000 1500 2000 2500 ia ib ic Fig 6: Phase current for LLLG fault (ABCG) at 25km. Fig 7: Triple Line To Earth Fault (ABCG) At 25 Km By Wavelet Transforms 0 500 1000 1500 2000 2500 3000 3500 4000 4500 -600 -400 -200 0 200 400 600 800 ia ib ic Fig 8: Phase Current For LG (AG)Fault At 50 Km Fig 9: Single line to earth fault (AG) at 50km
- 5. Detection And Location Of Faults In 11kv Underground Cable Using Continuous Wavelet… DOI: 10.9790/1676-10144450 www.iosrjournals.org 48 | Page 0 500 1000 1500 2000 2500 3000 3500 4000 4500 -1500 -1000 -500 0 500 1000 1500 ia ib ic Fig 10: phase current for LLG (ABG)fault at 50 km Fig 11: Double line to earth fault (ABG) at 50km 0 500 1000 1500 2000 2500 3000 3500 4000 4500 -1500 -1000 -500 0 500 1000 1500 ia ib ic Fig 12: phase current for LLLG (ABCG)fault at 50 km Fig 13: Triple line to earth fault (ABCG) at 50km by wavelet transforms
- 6. Detection And Location Of Faults In 11kv Underground Cable Using Continuous Wavelet… DOI: 10.9790/1676-10144450 www.iosrjournals.org 49 | Page Table-1 LG Fault Actual Distance(km) Calculated Distance(km) % Error 25 24.81 0.38 50 50.12 -0.24 Table-2 LLG Fault Actual Distance(km) Calculated Distance(km) % Error 25 24.37 1.26 50 54.26 8.52 Table-3 IV. Conclusions Detection and location of faults are very important in the power system as they are the basic of protection of the power system. If detection and location of faults are not accurate the protective devices can not trip properly and required operation cannot be done, which may leads to damage of the large equipments. In this paper 11kv 50km long under ground cable was modeled using Mat lab simulink and simulation was carried at different fault points of 25km and 50 km with the fault resistance of 1Ω and continuous wavelet transform technique is applied to extract the transient current. The results are obtained with the sampling rate of 8000 Hz with a wavelet transform of Daubechies Db4.For the sampling period of 0.00125,For scale a of 11.4285 the output waveform will have a frequency of 50Hz. Fig 2, 4 and 6 shows phase currents of single line to earth fault (AG), double line to earth fault (ABG) and triple line to earth fault (ABCG) at 25 km with fault resistance of 1Ω.Fig 3,5and 7 shows the transient current extracted using the continuous wavelet transform for 25km with a fault resistance of 1Ω. Fig 8, 10 and 12 shows phase currents of single line to earth fault (AG), double line to earth fault (ABG) and triple line to earth fault (ABCG) at 50 km with fault resistance of 1ohm.Fig 9,11and 13 shows the transient current extracted using the continuous wavelet transform for 50 km with a fault resistance of 1Ω. The location of fault can be calculated from the equation (2), in the calculation of fault location 10μs sampling time is used , the difference between the transient signal arrival of first fault signal and arrival of the reflected fault signal is multiplied by 10μs.The velocity of travelling time in the cable as 1.9557x105 km/s,the distance to the fault from the calculated pint are tabulated in the Tables-1,Table-2 and Table-3. Acknowledgements The authors wish to gratefully acknowledge technical support for this research work by Smt. Dr. M. Suryakalavathi .Dept of E.E.E, J.N.T.U.HHyderbad , and her support for the completion of this work. and gratefully acknowledge to Dr.B.Ravindranath Reddy for his valuable suggestions in completions of this work Mr.G.Prashuram, Angel technology, Hyderabad for the provided support Last but not least the author thank the management of Sri Sivani College of Engineering for their great and continuous support for the completion of the research work References [1]. Kuan, K.K & Warwick, K. (1992) Real-Time Expert System for Fault Location on High Voltage Underground Distribution Cables. IEE Publications Proceedings-c, Vol. 139, No.3, pp. 235-240. [2]. Crossley P.A. and MacLaren P.G. (1983) Distance protection based on travelling waves. IEEE Transactions on Power Apparatus and System. Vol. PAS 102, No.9, September: 2971-2983. [3]. Ancell G.B. & Pahalawaththa N.C. (1994) Maximum likelihood estimation of fault location on transmission lines using travelling waves. IEEE Transactions on Power Delivery. Vol. 9, No. 2, April: 680-689. [4]. Jie Liang, Elangovan S., Devotta J.B.X. (1999) Adaptive travelling wave protection algorithm using two correlation functions. IEEE Transactions on Power Delivery. Vol. 14, No.1, January: 126-131. [5]. Bo Z.Q., Weller G., Redfern M.A. (1999) Accurate fault location technique for distribution system using fault-generated high- frequency transient voltage signals. IEE Proceedings - Generation, Transmission and Distribution. Volume 146, Issue 1, January: 73 – 79. [6]. Crossley P.A., Gale P.F, Aurangzeb M. (2001) Fault location using high frequency travelling waves measured at a single location on a transmission line. Developments in Power System Protection. Amsterdam, Holland, 9-12 April: 403-406. [7]. Elhaffar, A. and Lehtonen, M. (2004) Travelling waves based earth fault location in 400 kV transmission network using single end measurement. Large Engineering Systems Conference on Power Engineering. LESCOPE-04., 28-30 July: 53 – 56.
- 7. Detection And Location Of Faults In 11kv Underground Cable Using Continuous Wavelet… DOI: 10.9790/1676-10144450 www.iosrjournals.org 50 | Page [8]. Thomas, D.W.P., Christopoulos, C., Tang, Y., Gale, P., Stokoe, J. (2004) Single ended travelling wave fault location scheme based on wavelet analysis. Eighth IEE International Conference on Developments in Power System Protection, Volume 1, 5-8 April: 196 - 199. [9]. Zeng Xiangjun, Li, K.K., Liu Zhengyi, Yin Xianggen (2004) Fault location using traveling wave for power networks. Industry Applications Conference. 39th IAS Annual Meeting, 3-7 Oct.: 2426 - 2429. International Journal of Engineering and Technology, Vol. 6, No.2, 2009, pp. 90-95 ISSN 1823-1039 2009 FEIIC 95 [10]. Evrenosoglu, C.Y. and Abur, A. (2005) Travelling wave based fault location for teed circuits. IEEE Transactions on Power Delivery. Volume 20, Issue 2, Part 1, April: 1115 – 1121. [11]. Fernando H.M and Ali.A (1998) Fault Location using Wavelet. IEEE Transaction on Power Delivery, Vol.13, No Biographies Of Author D. Prabhavathi Born in 1976 august 27, her B.Tech degree from KSRM college of Engineering, kadapa , SV university, and M.Tech degree from SV university in the year 2003.She has specialized in Power Systems, High Voltage Engineering. She is currently working as Prof & HOD , Dept of EEE Sri Sivani Institute of Technology srikakulam, A.P. INDIA. Her research interests include Simulation studies on faults identification in UG cable of LT and HT, Fuzzy logic, High Voltage Engineering, Power Electronics and drives modeling and design for reactive power compensations etc she has 13 years of experience. K .Prakasam, Born in 1973 April 20, his B.Tech degree from K.S.R.M College of Engineering S.V University in 1997 and M.Tech degree from S.V University in the year 2004. He has specialized in Power Systems, High Voltage Engineering and Control Systems. His research interests include Simulation studies on very fast Transients of different power system equipment, Power quality, Fuzzy logic, Power Electronics and drives control, He has 16 years of experience. He is presently working as Prof and HOD of Dept of EEE, and Academic Director of Sri Sivani College of Engineering Srikakulam, A.P, INDIA. Dr. M. Surya Kalavathi, Born on 8th July 1966, Obtained her B.Tech degree from S.V. U. in 1988 and M.Tech from S.V.U. in the year 1992. Obtained her doctoral degree from JNTU, Hyderabad and Post Doctoral from CMU, USA. She is presently the Professor (EEE) in JNTUH College of Engineering, Kukatpally, Hyderabad. Published 16 Research Papers and presently guiding 5 Ph.D. Scholars. She has specialized in Power Systems, High Voltage Engineering and Control Systems. Her research interests include Simulation studies on Transients of different power system equipment. She has 18 years of experience. She has invited for various lectures in institutes. Bhumanapally. Ravindhranath Reddy, Born on 3rd September, 1969. Got his B.Tech in Electrical & Electronics Engineering from the J.N.T.U.A, College of Engg., Anantapur in the year 1991s Completed his M.Tech in Energy Systems in IPGSR of J.N.T.University Hyderabad in the year 1997. Obtained his doctoral degree from JNTU,Hyderabad. He is presently guiding PhD scholars.