Communication Assisted Fuzzy based Adaptive Protective Relaying Scheme for Microgrid

  • Bokka Krishna Chaitanya Department of Electrical Engineering, National Institute of Technology, Raipur, CG, India
  • Atul Kumar Soni Department of Electrical Engineering, National Institute of Technology, Raipur, CG, India
  • Anamika Yadav Department of Electrical Engineering, National Institute of Technology, Raipur, CG, India


This study proposes a communication assisted fuzzy based adaptive protective relaying scheme for fault detection, faultclassification and faulty phase identification of microgrid along with a solution to isolate the microgrid from the utility grid bydisconnecting the static-switch. Any fault in the utility grid causes the microgrid to be isolated from the utility grid whereasif there is a fault in the microgrid it continues to operate with the utility grid. An adaptive fuzzy inference system has beendeveloped using a separate fuzzy rule base for the two modes of operation of microgrid, i.e. islanded mode or grid connectedmode. The Central Grid Status Communication System (CGSCU) is considered which monitors the status of PCC and sendsa command signal to the relays so that the relay settings are updated with new rules for any transition in the mode of themicrogrid. The fundamental phasor amplitude and zero sequence component of current signals are used as input features,fault detection, fault classification and faulty phase identification. A standard microgrid model IEC 61850-7-420 was simulatedusing MATLAB/SIMULINK. The proposed method is tested for all types of faults by varying fault parameters and also fordynamic situations such as connection/disconnection of DGs and loads. The test results substantiate the effectiveness of themethod.


[1] Y. Li, F. Nejabatkhah, Overview of control, integration and energy management
of microgrids, J. Mod. Power Sys. Clean Energy 2(3) (2014)
[2] B. S. Hartono, Y. Budiyanto, R. Setitabudy, Review of microgrid technology,
in: International Conference on QiR, 2013.
[3] N. D. Hatziargyriou, A. P. S. Meliopoulos, Distributed energy sources:
Technical challenges, in: IEEE Power Engineering Society Winter
Meeting, 2002.
[4] I. Sadeghkhani, M. E. H. Golshan, A. M. Sani, J. M. Guerrero,
A. Ketabi, Transient monitoring function–based fault detection for
inverter-interfaced microgrids, IEEE Transactions on Smart Griddoi:
[5] S. Kar, S. R. Samantaray, Time-frequency transform-based differential
scheme for microgrid protection, IET Generation, Transmission &
Distribution 8 (2) (2014) 310–320.
[6] A. Gururani, S. R. Mohanty, J. C. Mohanta, Microgrid protection using
hilbert–huang transform based-differential scheme, IET Generation,
Transmission & Distribution 10 (15) (2016) 3707–3716.
[7] D. P. Mishra, S. R. Samantaray, G. Joos, A combined wavelet and
data-mining based intelligent protection scheme for microgrid, IEEE
Transactions on Smart Grid 7 (5) (2016) 2295 – 2304.
[8] S. Kar, S. R. Samantaray, M. D. Zadeh, Data-mining model based intelligent
differential microgrid protection scheme, IEEE Systems Journal
11 (2) (2017) 1161 – 1169.
[9] W. K. A. Najy, H. H. Zeineldin, W. L. Woon, Optimal protection coordination
for microgrids with grid-connected and islanded capability, IEEE
Transactions On Industrial Electronics 60 (4) (2013) 1668 – 1677.
[10] E. Sortomme, S. S. Venkata, J. Mitra, Microgrid protection using
communication-assisted digital relays, IEEE Trans. Power Deliv 25 (4)
(2010) 2789–2796.
[11] M. A. Zamani, T. S. Sidhu, A. Yazdani, A protection strategy and
microprocessor-based relay for low-voltage microgrids, IEEE Transactions
On Power Delivery 26 (3) (2011) 1873–1883.
[12] H. Nikkhajoei, R. H. Lasseter, Microgrid protection, in: IEEE PES General
Meeting, 2007, pp. 24–28.
[13] U. Orji, C. Schantz, S. B. Leeb, J. L. Kirtley, B. Sievenpiper, K. Gerhard,
T. McCoy, Adaptive zonal protection for ring microgrids, IEEE
Transactions on Smart Grid 8 (4) (2017) 1843–1851.
[14] H. Muda, P. Jena, Superimposed adaptive sequence current based
microgrid protection: A new technique, IEEE Transactions on Power
Delivery 32 (2) (2017) 757–767.
[15] H. H. Zeineldin, E. F. El-Saadany, M. M. A. Salama, Distributed generation
microgrid operation: control and protection, in: Proc. Power Syst.
Conf, 2006, p. 105–112.
[16] E. Casagrande, W. L. Woon, H. H. Zeineldin, D. Svetinovic, A differential
sequence component protection scheme for microgrids with
inverter-based distributed generators, IEEE Transactions On Smart
Grid 5 (1) (2014) 29–37.
[17] T. S. Ustun, C. Ozansoy, A. Zayegh, Fault current coefficient and time
delay assignment for microgrid protection system with central protection
unit, IEEE Transactions On Power Systems 28 (2) (2013) 598–606.
[18] S. Cai, G. Liu, Study on application of fisher information * for power
system fault detection, Journal of Power Technologies (2016) 692–
[19] S. Mojtahedzadeh, S. N. Ravadanegh, M. R. Haghifam, A framework
for optimal clustering of a greenfield distribution network area into multiple
autonomous microgrids, Journal of Power Technologies 96 (4)
(2016) 219–228.
[20] T. S. Ustun, C. Ozansoy, A. Zayegh, Modeling of a centralized microgrid
protection system and distributed energy resources according to
iec 61850–7-420, IEEE Trans. Power Syst. 27 (3) (2012) 1560–1567.
— 69
How to Cite
CHAITANYA, Bokka Krishna; SONI, Atul Kumar; YADAV, Anamika. Communication Assisted Fuzzy based Adaptive Protective Relaying Scheme for Microgrid. Journal of Power Technologies, [S.l.], v. 98, n. 1, p. 57–69, apr. 2018. ISSN 2083-4195. Available at: <>. Date accessed: 28 sep. 2021.
Electrical Engineering


Microgrid, Fault Detection, Fault Classification, Fuzzy Inference System (FIS), Grid Connected Mode, Islanded Mode.

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.