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Cited by 229

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A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants

Open access
Hernandez, L., Baladron, C., Aguiar, J. M., Carro, B., Sanchez-Esguevillas, A., Lloret, Jaime, Chinarro, D., Gomez-Sanz, J. J., Cook, D.·2013·IEEE Communications Magazine

Abstract

Recent technological advances in the power generation and information technologies areas are helping to change the modern electricity supply system in order to comply with higher energy efficiency and sustainability standards. Smart grids are an emerging trend that introduce intelligence in the power grid to optimize resource usage. In order for this intelligence to be effective, it is necessary to retrieve enough information about the grid operation together with other context data such as environmental variables, and intelligently modify the behavior of the network elements accordingly. This article presents a multi-agent system model for virtual power plants, a new power plant concept in which generation no longer occurs in big installations, but is the result of the cooperation of smaller and more intelligent elements. The proposed model is not only focused on the management of the different elements, but includes a set of agents embedded with artificial neural networks for collaborative forecasting of disaggregated energy demand of domestic end users, the results of which are also shown in this article.

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Metadata

Authors
Hernandez, L., Baladron, C., Aguiar, J. M., Carro, B., Sanchez-Esguevillas, A., Lloret, J., Chinarro, D., Gomez-Sanz, J. J., & Cook, D.
Venue
IEEE Communications Magazine
Published
2013-01
Volume
51
Issue
1
Pages
106-113
ISSN
0163-6804 (ISSN-L)
OpenAlex
W2106030832
Cited by
229
References
0
FWCI
13.18
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants. https://app.cochat.ai/papers/10.1109/mcom.2013.6400446
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Hernandez, L., Baladron, C., Aguiar, J. M., Carro, B., Sanchez-Esguevillas, A., Lloret, J., Chinarro, D., Gomez-Sanz, J. J., & Cook, D. (2013). A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants. IEEE Communications Magazine. https://doi.org/10.1109/mcom.2013.6400446

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.