Skip to main content
Top

2023 | OriginalPaper | Chapter

High Impedance Fault Detection and Classification Based on Pattern Recognition

Authors : Zahra Moravej, Mehrdad Ghahremani

Published in: Modernization of Electric Power Systems

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

High-impedance faults (HIFs) occur in distribution networks due to contact between an electrified conductor and objects such as trees or conductor falling to the ground. In these cases, a small current flows in the conductor due to the low voltage in the network and the high impedance between the ground and the conductor. According to the conducted tests, the fault current amplitude can take a value between less than 1 A and 100 A. Protective devices are generally used to protect grid equipment, such as transformers or overhead and underground power lines, against fault currents exceeding the permissible values for this equipment. However, an HIF falls within these values; hence, conventional protections in distribution networks, such as overcurrent protection or ground fault protection, cannot detect this fault and do not damage this equipment. The main reason for detecting HIFs in traditional power grids is to prevent harm to persons as a result of electrocution. Moreover, the electric arc occurring due to the fault, especially when the conductor breaks and falls onto a tree, can result in fire. Early detection of this fault can prevent potential outages and reduce outage duration in distribution networks. Since the nature of an HIF depends on numerous parameters, such as feeder structure, ground structure, and humidity, the disturbance in the current and voltage waves of the feeder are diverse and unpredictable. This has prompted many researchers to propose various solutions for detecting HIFs and has resulted in the production of relays for this purpose. The present chapter book involves a thorough investigation of HIF detection schemes along with their advantages and disadvantages.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Aucoin B, Russell B (1982) Distribution high impedance fault detection utilizing high frequency current components. IEEE Trans Power Appar Syst 6:1596–1606CrossRef Aucoin B, Russell B (1982) Distribution high impedance fault detection utilizing high frequency current components. IEEE Trans Power Appar Syst 6:1596–1606CrossRef
2.
go back to reference Tengdin J, Westfall R (1994) High impedance fault detection technology report of PSRC working group D15 Tengdin J, Westfall R (1994) High impedance fault detection technology report of PSRC working group D15
3.
go back to reference Mortazavi S, Moravej Z, Shahrtash S (2018) A hybrid method for arcing faults detection in large distribution networks. Int J Electr Power Energy Syst 94:141–150CrossRef Mortazavi S, Moravej Z, Shahrtash S (2018) A hybrid method for arcing faults detection in large distribution networks. Int J Electr Power Energy Syst 94:141–150CrossRef
4.
go back to reference Kim CJ, Russell BD, Watson K (1990) A parameter-based process for selecting high impedance fault detection techniques using decision making under incomplete knowledge. IEEE Trans Power Delivery 5(3):1314–1320CrossRef Kim CJ, Russell BD, Watson K (1990) A parameter-based process for selecting high impedance fault detection techniques using decision making under incomplete knowledge. IEEE Trans Power Delivery 5(3):1314–1320CrossRef
5.
go back to reference Ghaderi A, Ginn III, Mohammadpour H (2017) A high impedance fault detection: a review. Electr Power Syst Res 143:376–388CrossRef Ghaderi A, Ginn III, Mohammadpour H (2017) A high impedance fault detection: a review. Electr Power Syst Res 143:376–388CrossRef
6.
go back to reference Patterson R, Tyska W, Russell B (1994) A microprocessor-based digital feeder monitor with high- impedance fault detection. No. CONF-941089-Vol. 1. USDOE, Washington, DC (United States); Korea Electric Power Corp. (KEPCO), Seoul (Korea, Republic of) Patterson R, Tyska W, Russell B (1994) A microprocessor-based digital feeder monitor with high- impedance fault detection. No. CONF-941089-Vol. 1. USDOE, Washington, DC (United States); Korea Electric Power Corp. (KEPCO), Seoul (Korea, Republic of)
7.
go back to reference Faridnia N, Samet H, Doostani Dezfuli B (2012) A new approach to high impedance fault detection based on correlation functions. In: IFIP international conference on artificial intelligence applications and innovations. Springer, Berlin, pp 453–462CrossRef Faridnia N, Samet H, Doostani Dezfuli B (2012) A new approach to high impedance fault detection based on correlation functions. In: IFIP international conference on artificial intelligence applications and innovations. Springer, Berlin, pp 453–462CrossRef
8.
go back to reference Russell B, Mehta K, Chinchali R (1988) Fault detection technique using low frequency current components-performance evaluation using recorded field data. IEEE Trans Power Delivery 3(4):1493–1500CrossRef Russell B, Mehta K, Chinchali R (1988) Fault detection technique using low frequency current components-performance evaluation using recorded field data. IEEE Trans Power Delivery 3(4):1493–1500CrossRef
9.
go back to reference Kim C, Russell B (1993) High-impedance fault detection system using an adaptive element model. IEE Proceedings C-Generation, Transmission and Distribution 140(2):153–159CrossRef Kim C, Russell B (1993) High-impedance fault detection system using an adaptive element model. IEE Proceedings C-Generation, Transmission and Distribution 140(2):153–159CrossRef
10.
go back to reference Sarlak M, Shahrtash S, Khaburi D (2010) Design and implementation of a systematically tunable high impedance fault relay. ISA Trans 49(3):358–368CrossRef Sarlak M, Shahrtash S, Khaburi D (2010) Design and implementation of a systematically tunable high impedance fault relay. ISA Trans 49(3):358–368CrossRef
11.
go back to reference Yang M, Gu J, Guan J (2005) Detection of downed conductor in distribution system. In: IEEE power engineering society general meeting Yang M, Gu J, Guan J (2005) Detection of downed conductor in distribution system. In: IEEE power engineering society general meeting
12.
go back to reference Etemadi A, Sanaye-Pasand M (2008) High-impedance fault detection using multi-resolution signal decomposition and adaptive neural fuzzy inference system. IET Gener Transm Distrib 2(1):110–118CrossRef Etemadi A, Sanaye-Pasand M (2008) High-impedance fault detection using multi-resolution signal decomposition and adaptive neural fuzzy inference system. IET Gener Transm Distrib 2(1):110–118CrossRef
13.
go back to reference Keyhani R, Deriche M, Palmer E (2001) A high impedance fault detector using a neural network and subband decomposition. In: Proceedings of the sixth international symposium on signal processing and its applications (Cat. No. 01EX467), vol 2 Keyhani R, Deriche M, Palmer E (2001) A high impedance fault detector using a neural network and subband decomposition. In: Proceedings of the sixth international symposium on signal processing and its applications (Cat. No. 01EX467), vol 2
14.
go back to reference Sultan A, Swift G, Fedirchuk D (1992) Detection of high impedance arcing faults using a multi-layer perceptron. IEEE Trans Power Delivery 7(4):1871–1877CrossRef Sultan A, Swift G, Fedirchuk D (1992) Detection of high impedance arcing faults using a multi-layer perceptron. IEEE Trans Power Delivery 7(4):1871–1877CrossRef
15.
go back to reference Lee R, Osborn R (1985) A microcomputer based data acquisition system for high impedance fault analysis. IEEE Trans Power Appar Syst 10:2748–2753CrossRef Lee R, Osborn R (1985) A microcomputer based data acquisition system for high impedance fault analysis. IEEE Trans Power Appar Syst 10:2748–2753CrossRef
16.
go back to reference Michalik M, Rebizant W, Lukowicz M, Lee S, Kang S (2005) Wavelet transform approach to high impedance fault detection in MV networks. In: IEEE Russia Power Tech Michalik M, Rebizant W, Lukowicz M, Lee S, Kang S (2005) Wavelet transform approach to high impedance fault detection in MV networks. In: IEEE Russia Power Tech
17.
go back to reference Michalik M, Rebizant W, Lukowicz M, Lee S, Kang S (2006) High-impedance fault detection in distribution networks with use of wavelet-based algorithm. IEEE Trans Power Delivery 21(4):1793–1802CrossRef Michalik M, Rebizant W, Lukowicz M, Lee S, Kang S (2006) High-impedance fault detection in distribution networks with use of wavelet-based algorithm. IEEE Trans Power Delivery 21(4):1793–1802CrossRef
18.
go back to reference Elkalashy N, Lehtonen M, Darwish H, Taalab A, Izzularab M (2007) DWT-based detection and transient power direction-based location of high-impedance faults due to leaning trees in unearthed MV networks. IEEE Trans Power Delivery 23(1):94–101CrossRef Elkalashy N, Lehtonen M, Darwish H, Taalab A, Izzularab M (2007) DWT-based detection and transient power direction-based location of high-impedance faults due to leaning trees in unearthed MV networks. IEEE Trans Power Delivery 23(1):94–101CrossRef
19.
go back to reference Gautam S, Brahma S (2012) Detection of high impedance fault in power distribution systems using mathematical morphology. IEEE Trans Power Syst 28(2):1226–1234CrossRef Gautam S, Brahma S (2012) Detection of high impedance fault in power distribution systems using mathematical morphology. IEEE Trans Power Syst 28(2):1226–1234CrossRef
20.
go back to reference Bakar A, Ali M, Tan C, Mokhlis H, Arof H, Illias H (2014) High impedance fault location in 11 kV underground distribution systems using wavelet transforms. Int J Electr Power Energy Syst 23:723–730CrossRef Bakar A, Ali M, Tan C, Mokhlis H, Arof H, Illias H (2014) High impedance fault location in 11 kV underground distribution systems using wavelet transforms. Int J Electr Power Energy Syst 23:723–730CrossRef
21.
go back to reference Kim C (2008) Electromagnetic radiation behavior of low-voltage arcing fault. IEEE Trans Power Delivery 24(1):416–423CrossRef Kim C (2008) Electromagnetic radiation behavior of low-voltage arcing fault. IEEE Trans Power Delivery 24(1):416–423CrossRef
22.
go back to reference Sharaf A, Snider L, Debnath, K (1993) A neural network based relaying scheme for distribution system high impedance fault detection. In: Proceedings 1993 the first New Zealand international two-stream conference on artificial neural networks and expert systems, pp 1226–1234 Sharaf A, Snider L, Debnath, K (1993) A neural network based relaying scheme for distribution system high impedance fault detection. In: Proceedings 1993 the first New Zealand international two-stream conference on artificial neural networks and expert systems, pp 1226–1234
23.
go back to reference Sharaf A, Wang G (2003) High impedance fault detection using feature-pattern based relaying. In: 2003 IEEE PES transmission and distribution conference and exposition (IEEE Cat. No. 03CH37495), vol 1, pp 222–226 Sharaf A, Wang G (2003) High impedance fault detection using feature-pattern based relaying. In: 2003 IEEE PES transmission and distribution conference and exposition (IEEE Cat. No. 03CH37495), vol 1, pp 222–226
24.
go back to reference Radojevic Z, Terzija V, Djuric N (2000) Numerical algorithm for overhead lines arcing faults detection and distance and directional protection. IEEE Trans Power Delivery 15(1):31–37CrossRef Radojevic Z, Terzija V, Djuric N (2000) Numerical algorithm for overhead lines arcing faults detection and distance and directional protection. IEEE Trans Power Delivery 15(1):31–37CrossRef
25.
go back to reference Michalik M, Lukowicz M, Rebizant W, Lee S, Kang S (2007) Verification of the wavelet-based HIF detecting algorithm performance in solidly grounded MV networks. IEEE Trans Power Delivery 22(4):2057–2064CrossRef Michalik M, Lukowicz M, Rebizant W, Lee S, Kang S (2007) Verification of the wavelet-based HIF detecting algorithm performance in solidly grounded MV networks. IEEE Trans Power Delivery 22(4):2057–2064CrossRef
26.
go back to reference Shahrtash S, Sarlak M (2006) High impedance fault detection using harmonics energy decision tree algorithm, In: International conference on power system technology, IEEE, pp 1–5 Shahrtash S, Sarlak M (2006) High impedance fault detection using harmonics energy decision tree algorithm, In: International conference on power system technology, IEEE, pp 1–5
27.
go back to reference Haghifam M, Sedighi A, Malik O (2006) Development of a fuzzy inference system based on genetic algorithm for high-impedance fault detection. IEE Proc-Gener Transm Distrib 153(3):359–367CrossRef Haghifam M, Sedighi A, Malik O (2006) Development of a fuzzy inference system based on genetic algorithm for high-impedance fault detection. IEE Proc-Gener Transm Distrib 153(3):359–367CrossRef
28.
go back to reference Baqui I, Zamora I, Mazón J, Buigues G (2011) High impedance fault detection methodology using wavelet transform and artificial neural networks. Electr Power Syst Res 81(7):1325–1333CrossRef Baqui I, Zamora I, Mazón J, Buigues G (2011) High impedance fault detection methodology using wavelet transform and artificial neural networks. Electr Power Syst Res 81(7):1325–1333CrossRef
29.
go back to reference Sarlak M, Shahrtash S (2011) SVM-based method for high-impedance faults detection in distribution networks. In: COMPEL-The international journal for computation and mathematics in electrical and electronic engineering Sarlak M, Shahrtash S (2011) SVM-based method for high-impedance faults detection in distribution networks. In: COMPEL-The international journal for computation and mathematics in electrical and electronic engineering
30.
go back to reference Moravej Z, Mortazavi S, Shahrtash S (2015) DT-CWT based event feature extraction for high impedance faults detection in distribution system. Int Trans Electr Energy Syst 25(12):3288–3303CrossRef Moravej Z, Mortazavi S, Shahrtash S (2015) DT-CWT based event feature extraction for high impedance faults detection in distribution system. Int Trans Electr Energy Syst 25(12):3288–3303CrossRef
31.
go back to reference Sarlak M, Shahrtash S (2011) High impedance fault detection using combination of multi-layer perceptron neural networks based on multi-resolution morphological gradient features of current waveform. IET Gener Transm Distrib 5(5):588–595CrossRef Sarlak M, Shahrtash S (2011) High impedance fault detection using combination of multi-layer perceptron neural networks based on multi-resolution morphological gradient features of current waveform. IET Gener Transm Distrib 5(5):588–595CrossRef
32.
go back to reference Bretas A, Moreto M, Salim R, Pires L (2006) A novel high impedance fault location for distribution systems considering distributed generation. In: IEEE/PES transmission and distribution conference and exposition: Latin America, pp 1–6 Bretas A, Moreto M, Salim R, Pires L (2006) A novel high impedance fault location for distribution systems considering distributed generation. In: IEEE/PES transmission and distribution conference and exposition: Latin America, pp 1–6
33.
go back to reference Sulaiman M, Tawfan A, Ibrahim Z (2013) Detecting high impedance fault in power distribution feeder with fuzzy subtractive clustering model. Aust J Basic Appl Sci 7(8):81–91 Sulaiman M, Tawfan A, Ibrahim Z (2013) Detecting high impedance fault in power distribution feeder with fuzzy subtractive clustering model. Aust J Basic Appl Sci 7(8):81–91
34.
go back to reference Torres-Garcia V, Guillen D, Olveres J, Escalante-Ramirez B, Rodriguez-Rodriguez J (2020) Modelling of high impedance faults in distribution systems and validation based on multiresolution techniques. Comput Electr Eng 83:106576CrossRef Torres-Garcia V, Guillen D, Olveres J, Escalante-Ramirez B, Rodriguez-Rodriguez J (2020) Modelling of high impedance faults in distribution systems and validation based on multiresolution techniques. Comput Electr Eng 83:106576CrossRef
35.
go back to reference Vijayachandran G, Mthew B (2013) Arcing fault detection in feeder networks using discrete wavelet transform and artificial neural network. Int J Emerg Sci Eng 1(10):93–102 Vijayachandran G, Mthew B (2013) Arcing fault detection in feeder networks using discrete wavelet transform and artificial neural network. Int J Emerg Sci Eng 1(10):93–102
36.
go back to reference Samantaray S, Panigrahi B, Dash P (2008) High impedance fault detection in power distribution networks using time–frequency transform and probabilistic neural network. IET Gener Transm Distrib 2(2):261–270CrossRef Samantaray S, Panigrahi B, Dash P (2008) High impedance fault detection in power distribution networks using time–frequency transform and probabilistic neural network. IET Gener Transm Distrib 2(2):261–270CrossRef
37.
go back to reference Kar S, Samantaray S (2014) Time-frequency transform-based differential scheme for microgrid protection. IET Gener Transm Distrib 8(2):310–320CrossRef Kar S, Samantaray S (2014) Time-frequency transform-based differential scheme for microgrid protection. IET Gener Transm Distrib 8(2):310–320CrossRef
38.
go back to reference Silva S, Costa P, Gouvea M, Lacerda A, Alves F, Leite D (2018) High impedance fault detection in power distribution systems using wavelet transform and evolving neural network. Electr Power Syst Res 154:474–483CrossRef Silva S, Costa P, Gouvea M, Lacerda A, Alves F, Leite D (2018) High impedance fault detection in power distribution systems using wavelet transform and evolving neural network. Electr Power Syst Res 154:474–483CrossRef
39.
go back to reference Ramos M, Bretas A, Bernardon D, Pfitscher L (2017) Distribution networks HIF location: a frequency domain system model and WLS parameter estimation approach. Electric power systems research, distribution networks HIF location: a frequency domain system model and WLS parameter estimation approach. Electr Power Syst Res 146:170–176CrossRef Ramos M, Bretas A, Bernardon D, Pfitscher L (2017) Distribution networks HIF location: a frequency domain system model and WLS parameter estimation approach. Electric power systems research, distribution networks HIF location: a frequency domain system model and WLS parameter estimation approach. Electr Power Syst Res 146:170–176CrossRef
40.
go back to reference Zhang S, Xiao X, He Z (2020) Detection of high-impedance fault in distribution network based on time–frequency entropy of wavelet transform. IEEJ Trans Electr Electron Eng 15(6):844–853CrossRef Zhang S, Xiao X, He Z (2020) Detection of high-impedance fault in distribution network based on time–frequency entropy of wavelet transform. IEEJ Trans Electr Electron Eng 15(6):844–853CrossRef
41.
go back to reference Snider L, Yuen Y (1998) The artificial neural-networks-based relay algorithm for the detection of stochastic high impedance faults. Neurocomputing 23(1–3):243–254CrossRef Snider L, Yuen Y (1998) The artificial neural-networks-based relay algorithm for the detection of stochastic high impedance faults. Neurocomputing 23(1–3):243–254CrossRef
42.
go back to reference Mohammadnian Y, Amraee T, Soroudi (2019) A fault detection in distribution networks in presence of distributed generations using a data mining–driven wavelet transform. IET Smart Grid 2(2):163–171CrossRef Mohammadnian Y, Amraee T, Soroudi (2019) A fault detection in distribution networks in presence of distributed generations using a data mining–driven wavelet transform. IET Smart Grid 2(2):163–171CrossRef
43.
go back to reference Silva S, Costa P, Santana M, Leite D (2020) Evolving neuro-fuzzy network for real-time high impedance fault detection and classification. Neural Comput & Applic 32(12):7597–7610CrossRef Silva S, Costa P, Santana M, Leite D (2020) Evolving neuro-fuzzy network for real-time high impedance fault detection and classification. Neural Comput & Applic 32(12):7597–7610CrossRef
44.
go back to reference Gadanayak D, Mallick R (2019) Interharmonics based high impedance fault detection in distribution systems using maximum overlap wavelet packet transform and a modified empirical mode decomposition. Int J Electr Power Energy Syst 112:282–293CrossRef Gadanayak D, Mallick R (2019) Interharmonics based high impedance fault detection in distribution systems using maximum overlap wavelet packet transform and a modified empirical mode decomposition. Int J Electr Power Energy Syst 112:282–293CrossRef
45.
go back to reference Ghaderi A, Mohammadpour H, Ginn H, Shin Y (2014) High-impedance fault detection in the distribution network using the time-frequency-based algorithm. IEEE Trans Power Delivery 30(3):1206–1268 Ghaderi A, Mohammadpour H, Ginn H, Shin Y (2014) High-impedance fault detection in the distribution network using the time-frequency-based algorithm. IEEE Trans Power Delivery 30(3):1206–1268
46.
go back to reference Sahoo S, Baran M (2014) A method to detect high impedance faults in distribution feeders. In: 2014 IEEE PES T&D conference and exposition, pp 1–6 Sahoo S, Baran M (2014) A method to detect high impedance faults in distribution feeders. In: 2014 IEEE PES T&D conference and exposition, pp 1–6
47.
go back to reference Sarwar M, Mehmood F, Abid M, Khan A, Gul S, Khan AS (2019) A High impedance fault detection and isolation in power distribution networks using support vector machines J King Saud University-Engineering Sci 32(2020): 524–535 Sarwar M, Mehmood F, Abid M, Khan A, Gul S, Khan AS (2019) A High impedance fault detection and isolation in power distribution networks using support vector machines J King Saud University-Engineering Sci 32(2020): 524–535
48.
go back to reference Jota F, Jota P (1998) High-impedance fault identification using a fuzzy reasoning system. IEE Proc-Gener Transm Distrib 145(6):656–661CrossRef Jota F, Jota P (1998) High-impedance fault identification using a fuzzy reasoning system. IEE Proc-Gener Transm Distrib 145(6):656–661CrossRef
49.
go back to reference Sekar K, Mohanty N (2020) A fuzzy rule base approach for high impedance fault detection in distribution system using morphology gradient filter. J King Saud University-Engineering Sci 32(3):177–185CrossRef Sekar K, Mohanty N (2020) A fuzzy rule base approach for high impedance fault detection in distribution system using morphology gradient filter. J King Saud University-Engineering Sci 32(3):177–185CrossRef
50.
go back to reference Sekar K, Mohanty N (2018) Data mining-based high impedance fault detection using mathematical morphology. Comput Electr Eng 69:129–141CrossRef Sekar K, Mohanty N (2018) Data mining-based high impedance fault detection using mathematical morphology. Comput Electr Eng 69:129–141CrossRef
Metadata
Title
High Impedance Fault Detection and Classification Based on Pattern Recognition
Authors
Zahra Moravej
Mehrdad Ghahremani
Copyright Year
2023
DOI
https://doi.org/10.1007/978-3-031-18996-8_16