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

Authors: Vincenzo Loia; Domenico Furno; Alfredo Vaccaro

Addresses: Department of Computer Science, University of Salerno, via Ponte Don Melillo, 84084 Fisciano, Salerno, Italy ' Department of Computer Science, University of Salerno, via Ponte Don Melillo, 84084 Fisciano, Salerno, Italy ' Department of Engineering, University of Sannio, Corso Garibaldi, 107, 82100 Benevento, Italy

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.

Keywords: decentralised smart grids; swarm intelligence; fuzzy data analysis; semantic technologies; smart grid monitoring; sensor data analysis; cooperative monitoring; power sensors.

DOI: 10.1504/IJSCC.2013.054144

International Journal of Systems, Control and Communications, 2013 Vol.5 No.1, pp.1 - 14

Received: 11 Sep 2012
Accepted: 01 Jan 2013
Published online: 12 Jul 2014 *

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