Probabilistic Topology Detection for Efficient MV-Micro Grid Control with Autarkic Smart Grid Systems

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CIRED 2018 Ljubljana WS - 0226 - 20988.pdf (445.38 KB)

Paper number

0226

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Conference name

CIRED 2018 Ljubljana Workshop

Conference date

7 - 8 June 2018

Conference location

Ljubljana, Slovenia

Peer-reviewed

Yes

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Convener

Authors

Modemann, Marcel, University of Wuppertal, Germany
Steinbusch, Philippe, University of Wuppertal, Germany
Uhlig, Roman, University of Wuppertal, Germany
Zdrallek, Markus, University of Wuppertal, Germany
Friedrich, Wolfgang, Phoenix Contact Energy Automation GmbH, Germany

Abstract

Due to political and economic goals, not only the German power grid is in a radical change. The classical top-down energy flow is continuously transforming into a bottom-up energy flow. Intelligent automation systems are increasingly important in this context. The smart grid systems and new developed functions induce an increasing flow of information, so-called micro-grids are supposed to regulate the power flow locally with a reduced data transfer. Such micro-grids can operate independently if it is able to decouple themselves from the power grid. In isolated operation, it is essential to recognize or record the exact breaker states so that the system define the limits of a micro-grid clearly. Although all breaker states are included in the SCADA (Supervisory Control and Data Acquisition), there is usually no connection between the SCADA and the automation system for IT security reasons, therefore the topology detection is essential [1]. Together with industrial partners, the University of Wuppertal is developing an automation system that could be operated in such a medium voltage (MV) micro-grid. The main focus of this paper is on the detection of different topology configurations in a MV micro-grid.

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Publisher

AIM

Date

2018-06-07

Published in

CIRED 2018 Ljubljana Workshop on Microgrids and Local Energy Communities

Permanent link to this record

https://www.cired-repository.org/handle/20.500.12455/1242
http://dx.doi.org/10.34890/395

ISSN

2032-9628

ISBN

978-2-9602415-1-8