Skip to main content

Identification of fault and section identification in multi-terminal HVDC system using unit protection scheme

Abstract

The Multi-Terminal Direct Current Transmission System (MTDC) is technically superior and economically more efficient than the AC transmission system, with a higher number of terminals providing access to remote power. The protection of MTDC transmission lines is essential for a smooth and reliable power supply. However, very few MTDC are operational today because of cost, control, and protection problems, especially because DC power lines are more susceptible to damage than AC lines. In this paper, we use one relay with single-ended data from the rectifier end to detect possible faults in the power line in the minimum amount of time. The proposed method is efficient as it can identify the faulty section and faulty pole with 100% accuracy. The reach setting of the proposed method is up to 100% of the line length.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Abbreviations

DC:

Direct current

AC:

Alternating current

HVDC:

High Voltage direct current

MTDC:

Multi-terminal HVDC

LCC:

Line-commutated converter

VSC:

Votage source converter

GTO:

Gate turn-off thyristor

IGBT:

Insulated gate bipolar transistor

FIS:

Fuzzy inference system

ANN:

Artificial neural network

TR:

Trip

TN:

Trip not

PG:

Pole to ground

PP:

Pole to pole

PPG:

Double pole to ground

References

  1. Abu-Elanien A (2018) Protection of star-connected multi-terminal HVDC systems with offshore wind farms, In: Proc IEEE 12th Int conf. on compatibility and power electronics and power engineering, Doha, Qatar

  2. Agarwal S, Swetapadma A, Panigrahi C, Dasgupta A (2019) A method for fault section identification in high voltage direct current transmission lines using one end measurements”. Electr Power Syst Res. https://doi.org/10.1016/j.epsr.2019.03.008

    Article  Google Scholar 

  3. Agarwal S, Swetapadma A, Panigarhi C (2018) An improved method using artificial neural network for fault detection and fault pole identification in voltage source convertor-based high-voltage direct current transmission lines, Arab J Sci Eng

  4. Agarwal S, Singh RK, Verma V (2020) Performance analysis of HVDC lines using surge arrester, IEEE/ICEFEET

  5. Agarwal S, Singh RK, Verma V (2021) Fault detection using harmonic analysis of single terminal DC current signal of HVDC Line, LNEE Book Series Springer/ ICETSGAI 4.0

  6. Ahmed N, Ram N, Memon AP, Ahmed S (2020) Comparative analysis of fault detection for HVDC transmission system using wavelet transform based on standard deviation, In: 3rd international conference on computing, mathematics and engineering technologies (iCoMET)

  7. Ankar SJ, Yadav A (2019) A novel approach to estimate fault location in current source converter–based HVDC transmission line by Gaussian process regression, Int Trans Electr Energy Syst

  8. Arnljotsson G (1999) Line Fault detection in HVDC transmission based on the Travelling wave principle, M.S. thesis, ITN, Linköpings Universitet

  9. Ayari M, Bichiou S, Belhaouane MM, Benhadj Braiek N (2019a) An advanced anti-windup control strategy for MMC-HVDC system. IETE J Res. https://doi.org/10.1080/03772063.2019.1676663

    Article  Google Scholar 

  10. Ayari M, Belhaouane MM, Benhadj Braiek N, Guillaud X (2019b) On the stabilization and stability domain estimation of VSC-HVDC transmission systems. IETE J Res. https://doi.org/10.1080/03772063.2019.1682068

    Article  Google Scholar 

  11. Blond S, Bertho R, Coury DV, Vieira JCM (2016) Design of protection schemes multi-terminal HVDC systems, Renew Sustain Energy Rev

  12. Bucher MK, Franck CM (2013) Contribution of fault current sources in multiterminal HVDC cable networks, IEEE Trans Power Deliv

  13. Curtis JB et al. (2012) Description of a protection plan for DC networks and preliminary results towards the real-time experimentation of a small-scale model of a DC network and the 120 kV DC breaker prototype tests, Twenties deliverable D11.2, EC-GA n° 249812

  14. Dallas I, Booth C (2014) Fault discrimination in multi-terminal DC Supergrids, In: CIGRÉ conference, innovation for secure and efficient transmission grids, Brussels

  15. Dallas I, Booth C (2014) Teleprotection in multi-terminal HVDC Supergrids, In: 12th IET international conference on developments in power system protection (DPSP 2014), Copenhagen

  16. Das TK, Chattopadhyay S, Das A (2021) String fault detection in solar photo voltaic arrays, IETE J Res

  17. Kar Ray D, Chattopadhyay S, Sengupta S (2018) Multi-resolution-analysis-based line-to-ground fault detection in a VSC-based HVDC system, IETE J Res

  18. Deenadayalan V, Vaishnavi P (2021) Improvised deep learning techniques for the reliability analysis and future power generation forecast by fault identification and remediation”. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-021-03086-z

    Article  Google Scholar 

  19. Descloux J et al. (2013) Protection system for meshed HVDC network using superconducting fault current limiters, IEEE Grenoble Power Tech (POWERTECH), Grenoble

  20. J. Descloux et al (2014) Protection algorithm based on differential voltage measurement for MTDC grids, In: 12th IET international conference on developments in power system protection (DPSP 2014), Copenhagen

  21. Farhadi M, Mohammed O (2016) Protection of multi-terminal and distributed DC systems: design challenges and techniques, Electr Power Syst Res

  22. Gupta J (2015) Applications of telemetry in power generation and distribution. IETE J Res 29(8):360–366

    Article  Google Scholar 

  23. Gupta V, Mittal M (2018) Blood pressure and ECG signal interpretation using neural network. Int J Appl Eng Res 13:127–132

    Google Scholar 

  24. Gupta V, Mittal M (2020) Arrhythmia detection in ECG signal using fractional wavelet transform with principal component analysis. J Inst Eng India Ser B 101(5):451–461

    Article  Google Scholar 

  25. Gupta V, Mittal M, Mittal V (2021) An efficient low computational cost method of r-peak detection. Wirel Pers Commun Int J. https://doi.org/10.1007/s11277-020-08017-3

    Article  Google Scholar 

  26. Harzelli I, Menacer A, Ameid T (2019) A fault monitoring approach using model-based and neural network techniques applied to input-output feedback linearization control induction motor”. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-019-01307-0

    Article  Google Scholar 

  27. He B et al. (2013) Research of bipolar HVDC transmission lines based on traveling wave differential protection,” TELKOMNIKA Indones. J Electr Eng

  28. Janarthanan R, Doss S, Balamurali R (2020) Robotic-based nonlinear device fault detection with sensor fault and limited capacity for communication. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-01946-8

    Article  Google Scholar 

  29. Johannesson N et al. (2016) Selective wave-front based protection algorithm for MTDC systems, In: 13th IET international conference on developments in power system protection (DPSP 2014), Edinburgh

  30. Kalpana V, Maheswar R, Nandakumar E (2020) Multiple parametric fault diagnosis using computational intelligence techniques in linear filter circuit. J Ambient Intell Humaniz Comput 11:5533–5545

    Article  Google Scholar 

  31. De Kerf K et al. (2011) Wavelet-based protection strategy for DC faults in multi-terminal VSC HVDC systems, IET Gener Transm Distrib

  32. Kobet G et al. (2010) Justifying pilot protection on transmission lines, In: 63rd annual conference for protective relay engineers, College Station, TX

  33. Kukker A, Sharma R, Malik H (2020) An intelligent genetic fuzzy classifier for transformer faults, IETE J Res

  34. Kumar R, Singh B, Kumar R, Marwaha S (2021) Online identification of underlying causes for multiple and multi-stage power quality disturbances using S-transform. IETE J Res. https://doi.org/10.1080/03772063.2021.1913073

    Article  Google Scholar 

  35. Kunlun H et al. (2011) Study on protective performance of HVDC transmission line protection with different types of line fault, In: 2011 4th international conference on electric utility deregulation and restructuring and power technologies (DRPT), Weihai

  36. Leterme W, Azad S, Hertem D (2018) HVDC grid protection algorithm design in-phase and modal domains, IET Renew Power Gener

  37. Li M, Chen K, He J, Luo Y, Wang X, Luo G, Zhang D (2020) Analysis of fault characteristics of hybrid multiterminal HVDC transmission system, In: 2nd international conference on smart power & internet energy systems (SPIES)

  38. Li R, Xu L, Yao L (2017) DC fault detection and location in meshed multiterminal HVDC systems based on DC reactor voltage change rate, IEEE Trans Power Deliv

  39. Liu L, Liu Z, Popov M, Palensky P, van der Meijden MA (2020) A fast protection of multi-terminal HVDC system based on transient signal detection, IEEE Trans Power Deliv

  40. Lu W, Ooi B (2002) Multi-terminal LVDC system for optimal acquisition of power in wind-farm using induction generators, IEEE Trans Power Electron

  41. Ma Y et al. (2013) Analysis of traveling wave protection criterion performance for double-circuit HVDC,” IEEE PES AsiaPacific power and energy engineering conference (APPEEC), Kowloon

  42. Barusu MR, Deivasigamani M (2020) Diagnosis of multiple rotor bar faults of squirrel cage induction motor (SCIM) using rational dilation wavelet transforms, IETE J Res

  43. Mankour M, Sami BS (2020) Mitigation of commutation failure method in LCC converter based on HVDC systems by mean of modeling and simulation. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-01924-0

    Article  Google Scholar 

  44. Mohanty B (2019) Hybrid fower pollination and pattern search algorithm optimized sliding mode controller for deregulated AGC system. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-019-01348-5

    Article  Google Scholar 

  45. Muniappan M (2021) A comprehensive review of DC fault protection methods in HVDC transmission systems. Prot Control Modern Power Syst. https://doi.org/10.1186/s41601-020-00173-9

    Article  Google Scholar 

  46. Naidoo D, Ijumba NM (2004) HVDC Line protection for the proposed future HVDC systems, In: international conference on power system technology (POWERCON), Singapore

  47. Naidoo D, Ijumba NM (2005) A protection system for long HVDC transmission lines, In: IEEE power engineering society inaugural conference and exposition in Africa, Durban

  48. Nair RKR, Pothiraj S, Nair TRR, Cengiz K (2021) An efficient partitioning and placement based fault TSV detection in 3D-IC using deep learning approach. J Ambient Intel Humaniz Comput. https://doi.org/10.1007/s12652-021-02964-w

    Article  Google Scholar 

  49. Pirooz Azad S et al. (2015) A DC grid primary protection algorithm based on current measurements, In: 17th european conference on power electronics and applications (EPE´15 ECCE-Europe), Geneva

  50. Ray PK, Panigrahi BK., Rout PK, Mohanty A, Eddy FY, Gooi HB (2018) Detection of islanding and fault disturbances in microgrid using wavelet packet transform,” IETE J Res

  51. Sahoo PK, Mohapatra S, Gupta DK, Panda S (2020) Multi-verse optimized fractional order PDPI controller for load frequency control. IETE J Res. https://doi.org/10.1007/s12652-019-01216-2

    Article  Google Scholar 

  52. Seshadrinath J, Singh B, Panigrahi BK (2014) A modified probabilistic neural network-based algorithm for detecting turn faults in induction machines. IETE J Res 58(4):300–309

    Article  Google Scholar 

  53. Shankar A, Sivakumar NR, Sivaram M, Ambikapathy A, Nguyen TK, Dhasarathan V (2020) Increasing fault tolerance ability and network lifetime with clustered pollination in wireless sensor networks. J Ambient Intell Humaniz Comput 12:2285–2298

    Article  Google Scholar 

  54. Sharma S, Ghosh S (2019) FIS and hybrid ABC-PSO based optimal capacitor placement and sizing for radial distribution networks. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-019-01216-2

    Article  Google Scholar 

  55. Shekhar H, Kumar J, Nayak A (2020) A Fault detection technique during power swing in a TCSC-compensated line using teager kaiser energy operator. IETE J Res. https://doi.org/10.1080/03772063.2020.1788427

    Article  Google Scholar 

  56. Shuo Z, Yongli L (2011) Simulation and analysis of HVDC line protection under the single pole to ground fault with high transition resistance, In: 4th international conference on electric utility deregulation and restructuring and power technologies (DRPT), Weihai

  57. Singh RK, Agarwal S, Verma V (2020) an improved method for fault analysis in asymmetrical high voltage direct current transmission lines, IEEE/UPCON 2019

  58. Swetapadma A, Agarwal S, Ranjan A, Abdelaziz AY (2021) A novel fault distance estimation method for voltage source converter-based HVDC transmission lines. Electr Power Comp Syst. https://doi.org/10.1080/15325008.2021.1908447

    Article  Google Scholar 

  59. Taimoor M, Aijun L, Samiuddin M (2020) Sliding mode learning algorithm-based adaptive neural observer strategy for fault estimation, detection and neural controller of an aircraft. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-02390-4

    Article  Google Scholar 

  60. Takeda et al. H (1995) New protection method for HVDC lines including cables,” IEEE Trans Power Deliv

  61. Venkateswaran M, Govindaraju C, Santhosh TK (2021) Capacitor voltage based predictive voltage control and fault diagnosis for four-port converter. J Ambient Intell Humanized Comput. https://doi.org/10.1007/s12652-021-03083-2

    Article  Google Scholar 

  62. Vyas B, Maheshwari RP, Das B (2014) Evaluation of artificial intelligence techniques for fault type identification in advanced series compensated transmission lines. IETE J Res. https://doi.org/10.1080/02564602.2014.893767

    Article  Google Scholar 

  63. Wadhwani S, Gupta SP, Kumar V (2014) Fault classification for rolling element bearing in electric machines. IETE J Res. https://doi.org/10.1007/s12652-019-01348-5

    Article  Google Scholar 

  64. Wang J et al. (2015) Multi-terminal DC system line protection requirement and high-speed protection solutions, CIGRÉ Symposium, Lund

  65. Wang M, Chai W, Xu C, Dong L, Li Y, Wang P, Qin X (2020) An edge computing method using a novel mode component for power transmission line fault diagnosis in distribution network. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-02466-1

    Article  Google Scholar 

  66. Xiang W, Yang S, Adam GP, Zhang H, Zuo W, Wen J (2021) DC fault protection algorithms of MMC-hvdc grids: fault analysis, methodologies, experimental validations, and future trends. IEEE Trans Power Electron. https://doi.org/10.1109/TPEL.2021.3071184

    Article  Google Scholar 

  67. Yang Q, Blond S, Aggarwal R, et al. (2017) New ANN method for multiterminal HVDC protection relaying, Electr Power Syst Res

  68. Yeap YM, Ukil A (2014) Wavelet-based fault analysis in HVDC system, school of electrical and electronic engineering, Nanyang technological university (NTU), Singapore, IEEE 2014

Download references

Funding

There is no funding.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Rakesh Kumar Singh.

Ethics declarations

Conflict of interest

There is no conflict of interest known to the authors.

Human or animal rights

The authors have complied with ethical standards. This research did not involve any human or animal participation.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Singh, R.K., Agarwal, S. & Verma, V. Identification of fault and section identification in multi-terminal HVDC system using unit protection scheme. Int J Syst Assur Eng Manag (2021). https://doi.org/10.1007/s13198-021-01444-w

Download citation

Keywords

  • Smoothing reactor
  • Section identification
  • Fault location
  • FIS
  • Fault resistance