Time-synchronized data collection in smart grids through IPv6 over BLE

Stanley Nwabuona, Konrad Diwold, Markus Schuss, Lukas Krammer, Simon Mayer, Alfred Einfalt

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

For the operation of electrical distribution system an increased shift towards smart grid operation can be observed. This shift provides operators with a high level of reliability and efficiency when dealing with highly dynamic distribution grids. Technically, this implies that the support for a bidirectional flow of data is critical to realizing smart grid operation, culminating in the demand for equipping grid entities (such as sensors) with communication and processing capabilities. Unfortunately, the retrofitting of brown-field electric substations in distribution grids with these capabilities is not straightforward - this scenario requires a solution that provides "industry-grade" Internet of Things capabilities at "consumer-grade" prices (e.g., off-the-shelf communication standards and hardware). In this paper, we discuss the particular challenge of precisely time-synchronized wireless data collection in secondary substations that at the same time supports on-site configuration by authorized maintenance personnel through a mobile application: to achieve this, we propose a combined implementation of IPv6 over Bluetooth Low Energy.

LanguageEnglish
Title of host publicationProceedings of the 8th International Conference on the Internet of Things, IoT 2018
PublisherAssociation of Computing Machinery
ISBN (Electronic)9781450365642
DOIs
StatusPublished - 15 Oct 2018
Event8th International Conference on the Internet of Things, IoT 2018 - Santa Barbara, United States
Duration: 15 Oct 201818 Oct 2018

Conference

Conference8th International Conference on the Internet of Things, IoT 2018
CountryUnited States
CitySanta Barbara
Period15/10/1818/10/18

Fingerprint

Electric substations
Retrofitting
Communication
Bluetooth
Personnel
Hardware
Sensors
Processing
Industry
Internet of things

Keywords

  • Dependable IoT
  • Smart Grid Automation
  • Time-synchronization
  • Wireless Communication

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Nwabuona, S., Diwold, K., Schuss, M., Krammer, L., Mayer, S., & Einfalt, A. (2018). Time-synchronized data collection in smart grids through IPv6 over BLE. In Proceedings of the 8th International Conference on the Internet of Things, IoT 2018 [a25] Association of Computing Machinery. DOI: 10.1145/3277593.3277632

Time-synchronized data collection in smart grids through IPv6 over BLE. / Nwabuona, Stanley; Diwold, Konrad; Schuss, Markus; Krammer, Lukas; Mayer, Simon; Einfalt, Alfred.

Proceedings of the 8th International Conference on the Internet of Things, IoT 2018. Association of Computing Machinery, 2018. a25.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Nwabuona, S, Diwold, K, Schuss, M, Krammer, L, Mayer, S & Einfalt, A 2018, Time-synchronized data collection in smart grids through IPv6 over BLE. in Proceedings of the 8th International Conference on the Internet of Things, IoT 2018., a25, Association of Computing Machinery, 8th International Conference on the Internet of Things, IoT 2018, Santa Barbara, United States, 15/10/18. DOI: 10.1145/3277593.3277632
Nwabuona S, Diwold K, Schuss M, Krammer L, Mayer S, Einfalt A. Time-synchronized data collection in smart grids through IPv6 over BLE. In Proceedings of the 8th International Conference on the Internet of Things, IoT 2018. Association of Computing Machinery. 2018. a25. Available from, DOI: 10.1145/3277593.3277632
Nwabuona, Stanley ; Diwold, Konrad ; Schuss, Markus ; Krammer, Lukas ; Mayer, Simon ; Einfalt, Alfred. / Time-synchronized data collection in smart grids through IPv6 over BLE. Proceedings of the 8th International Conference on the Internet of Things, IoT 2018. Association of Computing Machinery, 2018.
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