Cost-Efficient Low Latency Communication Infrastructure for Synchrophasor Applications in Smart Grids

Authors: Yang, B., Katsaros, K.V., Chai, W. and Pavlou, G.

http://eprints.bournemouth.ac.uk/24913/

Journal: IEEE Systems Journal

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

ISSN: 1932-8184

DOI: 10.1109/JSYST.2016.2556420

With the introduction of distributed renewable energy resources and new loads, such as electric vehicles, the power grid is evolving to become a highly dynamic system, that necessitates continuous and fine-grained observability of its operating conditions. In the context of the medium voltage (MV) grid, this has motivated the deployment of Phasor Measurement Units (PMUs), that offer high precision synchronized grid monitoring, enabling mission-critical applications such as fault detection/location. However, PMU-based applications present stringent delay requirements, raising a significant challenge to the communication infrastructure. In contrast to the high voltage domain, there is no clear vision for the communication and network topologies for the MV grid; a full fledged optical fiber-based communication infrastructure is a costly approach due to the density of PMUs required. In this work, we focus on the support of low-latency PMU-based applications in the MV domain, identifying and addressing the trade-off between communication infrastructure deployment costs and the corresponding performance. We study a large set of real MV grid topologies to get an in-depth understanding of the various key latency factors. Building on the gained insights, we propose three algorithms for the careful placement of high capacity links, targeting a balance between deployment costs and achieved latencies. Extensive simulations demonstrate that the proposed algorithms result in low-latency network topologies while reducing deployment costs by up to 80% in comparison to a ubiquitous deployment of costly high capacity links.

This data was imported from Scopus:

Authors: Yang, B., Katsaros, K.V., Chai, W.K. and Pavlou, G.

http://eprints.bournemouth.ac.uk/24913/

Journal: IEEE Systems Journal

Volume: 12

Issue: 1

Pages: 948-958

eISSN: 1937-9234

ISSN: 1932-8184

DOI: 10.1109/JSYST.2016.2556420

© 2016 IEEE. With the introduction of distributed renewable energy resources and new loads, such as electric vehicles, the power grid is evolving to become a highly dynamic system that necessitates continuous and fine-grained observability of its operating conditions. In the context of the medium voltage (MV) grid, this has motivated the deployment of phasor measurement units (PMUs), that offer high-precision synchronized grid monitoring, enabling mission-critical applications such as fault detection/location. However, PMU-based applications present stringent delay requirements, raising a significant challenge to the communication infrastructure. In contrast to the high voltage domain, there is no clear vision for the communication and network topologies for the MV grid; a full-fledged optical fiber-based communication infrastructure is a costly approach due to the density of PMUs required. In this study, we focus on the support of low-latency PMU-based applications in the MV domain, identifying and addressing the tradeoff between communication infrastructure deployment costs and the corresponding performance. We study a large set of real MV grid topologies to get an in-depth understanding of the various key latency factors. Building on the gained insights, we propose three algorithms for the careful placement of high capacity links, targeting a balance between deployment costs and achieved latencies. Extensive simulations demonstrate that the proposed algorithms result in low-latency network topologies while reducing deployment costs by up to 80% in comparison to a ubiquitous deployment of costly high capacity links.

This data was imported from Web of Science (Lite):

Authors: Yang, B., Katsaros, K.V., Chai, W.K. and Pavlou, G.

http://eprints.bournemouth.ac.uk/24913/

Journal: IEEE SYSTEMS JOURNAL

Volume: 12

Issue: 1

Pages: 948-958

eISSN: 1937-9234

ISSN: 1932-8184

DOI: 10.1109/JSYST.2016.2556420

The data on this page was last updated at 05:17 on May 25, 2020.