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  4. Grid watch dog: a stream reasoning approach for lightweight SCADA functionality in low-voltage grids
 
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Grid watch dog: a stream reasoning approach for lightweight SCADA functionality in low-voltage grids

Journal
Proceedings of the 8th International Conference on the Internet of Things (IOT 2018)
Type
book section
Date Issued
2018
Author(s)
Diwold, Konrad
Mayer, Simon  orcid-logo
Einfalt, Alfred
Parreira, Josiane Xavier
Hodges, Jack
Anicic, Darko
Mosshammer, Ralf
Abstract (De)
The advent of distributed energy resources in conjunction with recent developments in the context of smart embedded devices has fostered the increased integration of intelligent generators and prosumers into the energy system. As a consequence, previously passively operated grids have become highly dynamic environments, which require active monitoring and control. To allow for such monitoring and control, grid operators require lightweight SCADA-like functionality that can be flexibly adapted to dynamic grid contexts and is suitable for resource-constrained embedded systems. Grid Watch Dog enables system operators to create monitoring and control rules for low-voltage field devices on the fly, and to immediately deploy them in the field. The system combines a stream reasoner on field devices with an intuitive user interface for creating and managing rules. Grid Watch Dog has been implemented as a proof of concept in a smart grid testbed and we demonstrate its application in the context of monitoring a battery energy storage system.
Language
English
HSG Classification
contribution to scientific community
Refereed
Yes
Start page
12:1
End page
12:8
Event Title
Proceedings of the 8th International Conference on the Internet of Things, IOT 2018, Santa Barbara, CA, USA, October 15-18, 2018
Official URL
http://doi.acm.org/10.1145/3277593.3277601
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/101074
Subject(s)

computer science

Division(s)

ICS - Institute of Co...

Eprints ID
255799
File(s)
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Thumbnail Image

open.access

Name

Diwold-GWD-2018.pdf

Size

516.63 KB

Format

Adobe PDF

Checksum (MD5)

889a065d7664dae97ed3272e42a66a05

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