Statistics

    Map

Twitter

Fault Location in Power Transmission Lines using Autocorrelation Function
( Vol-5,Issue-5,May 2018 )
Author(s):

Danilo Pinto Moreira de Souza, Eliane da Silva Christo, Aryfrance Rocha Almeida, Kelly Alonso Costa

Keywords:

time series, line transmission, fault location, autocorrelation function (acf).

Abstract:

An electrical power system is subject to constant adversities due to its complexity, sensitivity and physical dimensions. Special emphasis is given to transmission lines (TL) that are the most vulnerable elements of an electrical system. Although most of the occurrences of distortions in the voltage signals from atmospheric discharges and overload are not detrimental to the energy supply, it is important to have control of these currents, since this allows the classification of the fault type and its geometric location on the transmission line. This study aims to compare different fault situations in a transmission line and to verify changes in time series models (TS). This study was carried out through computational tests performed with MatLAB®and RStudio® software. A total of 272faults were simulated in different situations. The obtained results were compared with the Traveling Wave Theory (TWT), another quite widespread fault localization technique. The above study revealed the applicability of time series in oscillographic data of fault situations in transmission lines with errors lower than 1.25%.

ijaers doi crossref DOI:

10.22161/ijaers.5.5.38

Paper Statistics:
  • Total View : 118
  • Downloads : 33
  • Page No: 296-304
Cite this Article:
MLA
Danilo Pinto Moreira de Souza et al ."Fault Location in Power Transmission Lines using Autocorrelation Function". International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),vol 5, no. 5, 2018, pp.296-304 AI Publications, doi:10.22161/ijaers.5.5.38
APA
Danilo Pinto Moreira de Souza, Eliane da Silva Christo, Aryfrance Rocha Almeida, Kelly Alonso Costa(2018).Fault Location in Power Transmission Lines using Autocorrelation Function. International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),5(5), 296-304. http://dx.doi.org/10.22161/ijaers.5.5.38
Chicago
Danilo Pinto Moreira de Souza, Eliane da Silva Christo, Aryfrance Rocha Almeida, Kelly Alonso Costa. 2018,"Fault Location in Power Transmission Lines using Autocorrelation Function". International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)).5(5):296-304. Doi: 10.22161/ijaers.5.5.38
Harvard
Danilo Pinto Moreira de Souza, Eliane da Silva Christo, Aryfrance Rocha Almeida, Kelly Alonso Costa. 2018,Fault Location in Power Transmission Lines using Autocorrelation Function, International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)).5(5), pp:296-304
IEEE
Danilo Pinto Moreira de Souza, Eliane da Silva Christo, Aryfrance Rocha Almeida, Kelly Alonso Costa."Fault Location in Power Transmission Lines using Autocorrelation Function", International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),vol.5,no. 5, pp.296-304,2018.
Bibtex
@article {danilopintomoreiradesouza2018fault,
title={Fault Location in Power Transmission Lines using Autocorrelation Function},
author={Danilo Pinto Moreira de Souza, Eliane da Silva Christo, Aryfrance Rocha Almeida, Kelly Alonso Costa},
journal={International Journal of Advanced Engineering Research and Science},
volume={5},
year= {2018},
}
Share:
References:

[1] Costa, F. F., Formiga, D. A., Ferreira, R. R., Sousa, T., & Costa, F. B. (2013, June). A recursive least-squares aided by pre-filtering for phasor-estimation in distance protection. In PowerTech (POWERTECH), 2013 IEEE Grenoble (pp. 1-6). IEEE.
[2] Agarwall, N., Mahela, O., & Kumar, B. (2016). Detection of power system faults in the presence of linear loads using stockwell transform. Journal of Electrical and Electronics Engineering, 2, 37-45.
[3] Costa, F. B., Souza, B. A., & Brito, N. S. D. (2009, June). A wavelet-based method for detection and classification of single and crosscountry faults in transmission lines. In International Conference on Power Systems Transients (pp. 1-8).
[4] Suresh, S., Nagarajan, R., Sakthivel, L., Logesh, V., Mohandass, C., &Tamilselvan, G. (2017).Transmission Line Fault Monitoring and Identification System by Using Internet of Things. International Journal of Advanced Engineering Research and Science (IJAERS), 4, 9-14.
[5] Robertson, D. C., Camps, O. I., Mayer, J. S., & Gish, W. B. (1996). Wavelets and electromagnetic power system transients. IEEE Transactions on Power Delivery, 11(2), 1050-1058.
[6] Li, J., Yang, Q., Mu, H., Le Blond, S., & He, H. (2018). A new fault detection and fault location method for multi-terminal high voltage direct current of offshore wind farm. Applied Energy, 220, 13-20.
[7] El Halabi, N., García-Gracia, M., Borroy, J., & Villa, J. L. (2011). Current phase comparison pilot scheme for distributed generation networks protection. Applied Energy, 88(12), 4563-4569.
[8] Jia, K., Gu, C., Li, L., Xuan, Z., Bi, T., & Thomas, D. (2018). Sparse voltage amplitude measurement based fault location in large-scale photovoltaic power plants. Applied Energy, 211, 568-581.
[9] Shankaraiah, R &Shankaraiah (2016). Analysis of Voltage Sag in Sub Transmission System. International Journal of Advanced Engineering Research and Science (IJAERS), 3, 9-13
[10] Paithankar, Y. G., &Sant, M. T. (1985). A new algorithm for relaying and fault location based on autocorrelation of travelling waves. Electric Power Systems Research, 8(2), 179-185.
[11] Sadeh, J., &Afradi, H. (2009). A new and accurate fault location algorithm for combined transmission lines using adaptive network-based fuzzy inference system. Electric Power Systems Research, 79(11), 1538-1545.
[12] Cavalcante, P. A., Trindade, F. C., & de Almeida, M. C. (2013). Transmission Lines Fault Location: A Mathematical Morphology-Based Approach. Journal of Control, Automation and Electrical Systems, 24(4), 470-480.
[13] Prakasam, D. K., Suryakalavathi, D. M. & Reddy, M. R. (2015). Detection and location of faults in 11kv underground cable by using continuous wavelet transform (cwt). Journal of Electrical and Electronics Engineering, 10, 44-50.
[14] Souza, T. B. P. (2007). Análise de Ondas Viajantes em Linhas de Transmissão para Localização de Faltas: Abordagem via Transformada Wavelet (Doctoraldissertation, Master’sThesis, Federal Universityof Pará (UFPA): Belém, Brazil, 2007.(In Portuguese)).
[15] Marti, J. R. (1982). Accuarte modelling of frequency-dependent transmission lines in electromagnetic transient simulations. IEEE transactions on power apparatus and systems, (1), 147-157.
[16] Souza, S. C. A., Braga, A. P. S., Leão, R. P. S., Almeida, O. M. A., Almeida, A. R., & Abreu, F. C. M. Uso de Redes Neurais Artificiais e Transformada de Stockwell na Localização de Faltas em Linhas de Transmissão; Universidade Federal do Ceará (UFC): Fortaleza, Brazil, 2015. Google Scholar.
[17] Crăciun, M., Vamoş, C., &Suciu, N. (2018). Analysis and generation of groundwater concentration time series. Advances in Water Resources, 111, 20-30.
[18] de Oliveira Silva, R., da Silva Christo, E., & Alonso Costa, K. (2014). Analysis of Residual Autocorrelation in Forecasting Energy Consumption through a Java Program. In Advanced Materials Research (Vol. 962, pp. 1753-1756). Trans Tech Publications.
[19] de Jesus, J. C., da Silva Christo, E., da Silva Garcia, V., & Alvarez, G. B. (2016). Time Series Analysis For Modeling Of Glioma Growth In Response To Radiotherapy. IEEE Latin America Transactions, 14(3), 1532-1537.
[20] Deb, C., Zhang, F., Yang, J., Lee, S. E., & Shah, K. W. (2017). A review on time series forecasting techniques for building energy consumption. Renewable and Sustainable Energy Reviews, 74, 902-924.
[21] Cox, D. R., & Stuart, A. (1955). Some quick sign tests for trend in location anddispersion. Biometrika, 42(1/2), 80-95.
[22] Pinto Moreira de Souza, D., da Silva Christo, E., & Rocha Almeida, A. (2017). Location of Faults in Power Transmission Lines Using the ARIMA Method. Energies, 10(10), 1596.
[23] Cantanheda, S. S. T. (2011). Localização de faltas em linhas de transmissão por meio de ondas viajantes (Master'sthesis, Federal Universityof Piauí).