RT Journal Article
T1 Adaptive Reclosing Technique Using Variational Mode Decomposition Algorithm in BESS-Based Microgrid
A1 Chandrakar, Ruchi
A1 Biswal, Monalisa
A1 Kishor, Nand
A1 Panigrahi, Bijaya Ketan
A1 Perez-Basante, Angel
A1 Rodriguez-Seco, J. Emilio
AB This study introduces a novel adaptive technique to accelerate the process of reclosing in a Battery Energy Storage System (BESS)-based microgrid system to provide uninterrupted power supply (UPS). Two different methodologies, Fault Current Contribution Ratio (FCCR) and Variational Mode Decomposition (VMD) are used to implement the proposed technique. First, the FCCR between the healthy and faulty phases is estimated in the relay after the occurrence of the transient. In the next stage, exact fault occurrences and clearance instances are detected using the VMD technique. The exact detection of fault clearance time will help reduce the conventional outage time. This will reduce the unwanted burden on the BESS as it can be used adaptively during the fault only. The comparative assessment is done to show the efficacy of the proposed reclosing method. The proposed technique will also help distinguish faults from switching operations. The performance of the proposed method is validated through a modified IEEE 13-bus BESS-based microgrid architecture. The EMTDC/PSCAD software is used for simulation. The algorithms are developed on the MATLAB platform. Real-time test results are also provided for the signals obtained from the Smart Grid Technology Laboratory (SGTL) lab setup. The results prove the efficacy of the proposed technique.
SN 2169-3536
YR 2023
FD 2023
LK https://hdl.handle.net/11556/4585
UL https://hdl.handle.net/11556/4585
LA eng
NO Chandrakar , R , Biswal , M , Kishor , N , Panigrahi , B K , Perez-Basante , A & Rodriguez-Seco , J E 2023 , ' Adaptive Reclosing Technique Using Variational Mode Decomposition Algorithm in BESS-Based Microgrid ' , IEEE Access , vol. 11 , pp. 91133-91144 . https://doi.org/10.1109/ACCESS.2023.3307433
NO Publisher Copyright: © 2013 IEEE.
NO This work was supported by the European Research Infrastructure supporting Smart Grid and Smart Energy Systems Research, Technology Development, Validation and Roll Out (ERIGRID) Research Infrastructure through the European Union's Horizon 2020 Research and Innovation Programme under Grant 654113.
DS TECNALIA Publications
RD 28 jul 2024