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Decentralised smart grids monitoring by swarm-based semantic sensor data analysis

Decentralised smart grids monitoring by swarm-based semantic sensor data analysis The large-scale deployment of the smart grids paradigm is expected to support the evolution of traditional electrical power systems toward active, flexible and self-healing web energy networks composed by distributed and cooperative energy resources. In this field, the application of hierarchical monitoring paradigms has many disadvantages that could hinder their application in modern smart grids where the constant growth of grid complexity and the need for supporting rapid decisions in a data rich, but information limited environment, require more scalable, more flexible monitoring paradigms. In trying and addressing these challenges, in this paper, a distributed and cooperative monitoring architecture aimed at exploiting the semantic representation of power system measurements for automatically detecting anomalies and incoherencies in power sensors data is proposed. Numerical results, obtained on the 57 bus IEEE test network, demonstrate the effectiveness of the proposed framework. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Systems, Control and Communications Inderscience Publishers

Decentralised smart grids monitoring by swarm-based semantic sensor data analysis

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References (25)

Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1755-9340
eISSN
1755-9359
DOI
10.1504/IJSCC.2013.054144
Publisher site
See Article on Publisher Site

Abstract

The large-scale deployment of the smart grids paradigm is expected to support the evolution of traditional electrical power systems toward active, flexible and self-healing web energy networks composed by distributed and cooperative energy resources. In this field, the application of hierarchical monitoring paradigms has many disadvantages that could hinder their application in modern smart grids where the constant growth of grid complexity and the need for supporting rapid decisions in a data rich, but information limited environment, require more scalable, more flexible monitoring paradigms. In trying and addressing these challenges, in this paper, a distributed and cooperative monitoring architecture aimed at exploiting the semantic representation of power system measurements for automatically detecting anomalies and incoherencies in power sensors data is proposed. Numerical results, obtained on the 57 bus IEEE test network, demonstrate the effectiveness of the proposed framework.

Journal

International Journal of Systems, Control and CommunicationsInderscience Publishers

Published: Jan 1, 2013

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