Non-Recursive System Identification and Fault Detection in LVDC and ELVDC Grids

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Strobl C, Schäfer M, Rabenstein R
Publication year: 2018
Language: English


Abstract


Low end extra low voltage direct current grids

require selective fault protection designed for the specific application

and system voltage. System identification and machine

learning methods are helpful to identify, to localize and to classify

occurring fault events. A category of non-recursive large-signal

methods in the time domain for system identification and for

refined fault detection and analysis is introduced.



FAU Authors / FAU Editors

Rabenstein, Rudolf Prof. Dr.
Technische Fakultät
Schäfer, Maximilian
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


External institutions
E-T-A Elektrotechnische Apparate GmbH


How to cite

APA:
Strobl, C., Schäfer, M., & Rabenstein, R. (2018). Non-Recursive System Identification and Fault Detection in LVDC and ELVDC Grids. Florence, IT.

MLA:
Strobl, Christian, Maximilian Schäfer, and Rudolf Rabenstein. "Non-Recursive System Identification and Fault Detection in LVDC and ELVDC Grids." Proceedings of the IEEE Int. Symp. on Circuits and Systems (ISCAS), Florence 2018.

BibTeX: 

Last updated on 2018-10-08 at 22:28