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Authors: Roman Denysiuk 1 ; Fabio Lilliu 2 ; Meritxell Vinyals 1 and Diego Reforgiato Recupero 2 ; 3

Affiliations: 1 CEA, LIST, 91191 Gif-sur-Yvette, France ; 2 Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, Cagliari, Italy ; 3 R2M Solution s.r.l., Polo Tecnologico di Pavia, Via Fratelli Cuzio, 42, 27100, Pavia, Italy

Keyword(s): Multiagent System, Local Energy Community, Demand Response.

Abstract: Local energy communities (LECs) represent a shift in energy management from an individual approach towards a collective one. LECs can reduce energy costs for end-users and contribute to meeting climate objectives through the use of renewable energy. This paper presents the application of a multiagent system (MAS) approach to realize the concept of LEC in a real-world scenario involving a community of households. An appropriate agent-based model for the given community is presented. This model effectively distributes the tasks among the agents considering electrical and heat energy flows. The agent coordination mechanism is based on the Alternative Direction Method of Multipliers. The obtained results provide evidence of the validity of the developed MAS and show its potential to increase a total social welfare of the community.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Denysiuk, R.; Lilliu, F.; Vinyals, M. and Recupero, D. (2020). Multiagent System for Community Energy Management. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-395-7; ISSN 2184-433X, SciTePress, pages 28-39. DOI: 10.5220/0008914200280039

@conference{icaart20,
author={Roman Denysiuk. and Fabio Lilliu. and Meritxell Vinyals. and Diego Reforgiato Recupero.},
title={Multiagent System for Community Energy Management},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2020},
pages={28-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008914200280039},
isbn={978-989-758-395-7},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Multiagent System for Community Energy Management
SN - 978-989-758-395-7
IS - 2184-433X
AU - Denysiuk, R.
AU - Lilliu, F.
AU - Vinyals, M.
AU - Recupero, D.
PY - 2020
SP - 28
EP - 39
DO - 10.5220/0008914200280039
PB - SciTePress

- Science and Technology Publications, Lda.
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