Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Application of μPMUs for adaptive protection of overcurrent relays in microgrids

This study proposes a new application of micro-phasor measurement units (µPMUs) for adaptive coordination of overcurrent relays in microgrids. Mis-coordination of overcurrent relays usually arising from the variation of relays fault current and it can cause damage to equipment of network and raise operating costs. Fault current injection and direction to microgrid are highly dependent on network uncertainties; therefore, fault current is affected by line and power plant outages. This study proposes an algorithm to detect these uncertainties in online operation. Then, microgrid overcurrent relays coordination is optimised again. Uncertainties are line and power plant outages in transmission network and microgrid side and two distinct methods are used for each. For online detection of uncertainties in the transmission side, it is assumed that a µPMU is installed between transmission network and microgrid point of common coupling; so, the topology changes such as line outage is detected by monitoring of Thevenin impedance estimation that is obtained by µPMU measurements. Uncertainties detection in a microgrid is done by signals that are sent by µPMUs and installed all over the microgrid. All data are gathered and analysed in phasor data concentrators and then overcurrent relays coordination is updated with such changes.

References

    1. 1)
      • 19. Motavalian, A.R., Moadabi, N., Gharehpetian, G.B.: ‘Reliability assessment of power system back up protection in smart grid control center using phasor measurement units (PMU)’. Int. Conf. Renewable Energies and Power Quality, Bilbao, Spain, March 2013, pp. 17.
    2. 2)
      • 17. Wang, Y.J., Liu, C.W., Liu, Y.H.: ‘A PMU based special protection scheme: a case study of Taiwan power system’, Int. J. Electr. Power Energy Syst., 2005, 27, (3), pp. 215223.
    3. 3)
      • 21. Jampala, A.K., Venkata, S.S., Damborg, M.J.: ‘Adaptive transmission protection: concepts and computational issues’, IEEE Trans. Power Deliv., 1989, 4, (1), pp. 177185.
    4. 4)
      • 2. Zhang, G., Sun, K., Chen, H., et al: ‘Application of synchrophasor measurements for improving operator situational awareness’. IEEE PES General Meeting, Detroit, MI, July 2011, pp. 2429.
    5. 5)
      • 24. ElHalabi, N.: ‘Current phase comparison pilot scheme for distributed generation networks protection’, Appl. Energy, 2011, 88, (12), pp. 45634569.
    6. 6)
      • 12. Von Meier, A., Stewart, E., McEachern, A., et al: ‘Precision micro-synchrophasors for distribution systems: a summary of applications systems’, IEEE Trans. Smart Grid, 2017, 8, (6), pp. 292620936.
    7. 7)
      • 14. ARPA-E.: ‘Diagnostic applications for micro-synchrophasor measurements’ (CIEE, Berkeley, CA, USA, 2014).
    8. 8)
      • 6. Sun, K., Luo, X., Wong, J.: ‘Early warning of wide-area angular stability problems using synchrophasors’. IEEE PES General Meeting, San Diego, USA, July 2012, pp. 2326.
    9. 9)
      • 11. Von Meier, A., Culler, D., McEachern, A., et al: ‘Micro-synchrophasors for distribution systems’. IEEE Innovative Smart Grid Technologies Conference, Washington, DC, USA, February 2014.
    10. 10)
      • 18. Saran, A.: ‘Comparison between overcurrent relay and developed PMU based protection’. North American Power Symp. (NAPS), Manhattan, USA, September 2013.
    11. 11)
      • 7. Kaci, A., Kamwa, I., Dessaint, S.A., et al: ‘Synchrophasor data baselining and mining for online monitoring of dynamic security limits’, IEEE Trans. Power Syst., 2014, 29, (6), pp. 26812695.
    12. 12)
      • 25. Razavi, F., Abyaneh, H.A., Al-Dabbagh, M., et al: ‘A new comprehensive genetic algorithm method for optimal overcurrent relays coordination’, Electr. Power Syst. Res., 2008, 78, (4), pp. 713720.
    13. 13)
      • 15. Liao, A., Stewart, E., Kara, E.: ‘Micro-synchrophasor data for diagnosis of transmission and distribution level events’. IEEE/PES Transmission and Distribution Conf. and Exposition (TD), Dallas, USA, May 2016, pp. 15.
    14. 14)
      • 9. LBNL-6866E: ‘Using micro-synchrophasor data for advanced distribution grid planning and operations analysis’, 2014.
    15. 15)
      • 20. North American SynchroPhasor Initiative.: ‘Synchrophasor monitoring for distribution systems: technical foundations and applications’ (NASPI, Albuquerque, NM, USA, 2018).
    16. 16)
      • 3. US–Canada Power System.: ‘Final report on the 14 August 2003 blackout in the United States and Canada: causes and recommendations’. Outage Task Force, 2004.
    17. 17)
      • 1. NERC.: ‘Real-time application of synchrophasors for improving reliability’, 2010, pp. 3768.
    18. 18)
      • 13. Arghandeh, R., Bradly, K., von Meier, A.: ‘Micro synchrophasors for power distribution systems’, IET Eng. Technol. Ref., 2016, 16, pp. 118.
    19. 19)
      • 26. Bahadornejad, M., Ledwich, G.: ‘System Thevenin impedance estimation using signal processing on load bus data’. Proc. Sixth Int. Conf. Advances in Power System Control, Operation and management, APSCOAI, Hong Kong, China, November 2003, pp. 274279.
    20. 20)
      • 16. Ghalei Monfared Zanjani, M., Kazemi Kargar, H., Ghalei Monfared Zanjani, M.: ‘High impedance fault detection of distribution network by phasor measurement units’. Electrical Power Distribution Networks (EPDC), Tehran, Iran, May 2012, pp. 15.
    21. 21)
      • 5. Ghanavati, G., Hines, P., Lakoba, T.: ‘Investigating early warning signs of oscillatory instability in simulated phasor measurements’. Proc. IEEE PES General Meeting, MD, USA, July 2014, pp. 15.
    22. 22)
      • 8. IEEE Smart Grid Newsletters: ‘Opportunities and challenges for PMU deployment in distribution systems’, 2014.
    23. 23)
      • 23. Myrda, P.T., Kellner, K.: ‘NASPInet – the Internet for synchrophasors’. 43rd Hawaii Int. Conf. System Sciences (HICSS), Honolulu, USA, June 2010, pp. 16.
    24. 24)
      • 22. Thorp, J.S., Adamiak, M., Banerjee, H.N., et al: ‘Feasibility of adaptive protection and control’, IEEE Trans. Power Deliv., 1993, 8, (3), pp. 975983.
    25. 25)
      • 10. Andersen, M., Kumar, S., Brooks, C., et al: ‘DISTIL: design and implementation of a scalable synchrophasor data processing system’. IEEE Conf. Smart Grid Communications, Miami, USA, November 2015.
    26. 26)
      • 4. Ghanavati, G., Hines, P., Lakoba, T.I.: ‘Identifying useful statistical indicators of proximity to instability in stochastic power systems’, IEEE Trans. Power Syst., 2016, 31, (2), pp. 13601368.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2018.5898
Loading

Related content

content/journals/10.1049/iet-gtd.2018.5898
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address