An Agent-based Approach for Smart Energy Grids

Alba Amato, Beniamino Di Martino, Marco Scialdone, Salvatore Venticinque

2014

Abstract

The increasing demand for energy and the availability of several solutions of renewable energy sources has stimulated the formulation of plans aiming at expanding and upgrading existing power grids in several countries. According to NIST, smart grid will be one of the greatest achievements of the 21st century. By linking information technologies with the electric power grid to provide electricity with a brain, the smart grid promises many benefits, including increased energy efficiency, reduced carbon emissions, and improved power reliability. In this paper we present an agent based architecture for supporting collection and processing of information about local energy production and storage resources of neighborhoods of individual houses and to schedule the energy flows using negotiation protocols.

Download


Paper Citation


in Harvard Style

Amato A., Di Martino B., Scialdone M. and Venticinque S. (2014). An Agent-based Approach for Smart Energy Grids . In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-016-1, pages 164-171. DOI: 10.5220/0004820001640171

in Bibtex Style

@conference{icaart14,
author={Alba Amato and Beniamino Di Martino and Marco Scialdone and Salvatore Venticinque},
title={An Agent-based Approach for Smart Energy Grids},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2014},
pages={164-171},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004820001640171},
isbn={978-989-758-016-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - An Agent-based Approach for Smart Energy Grids
SN - 978-989-758-016-1
AU - Amato A.
AU - Di Martino B.
AU - Scialdone M.
AU - Venticinque S.
PY - 2014
SP - 164
EP - 171
DO - 10.5220/0004820001640171