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Authors: Mohamed-Harith Ibrahim 1 ; 2 ; Stéphane Lecoeuche 1 ; Jacques Boonaert 1 and Mireille Batton-Hubert 2

Affiliations: 1 IMT Nord Europe, Institut Mines-Télécom, Univ. Lille, Centre for Digital Systems, F-59000 Lille, France ; 2 Mines Saint-Etienne, Univ Clermont Auvergne, CNRS, UMR 6158 LIMOS, Institut Henri Fayol, F-42023, Saint Etienne, France

Keyword(s): Multi-Objective Reinforcement Learning, Deep Reinforcement Learning, Electric Water Heater.

Abstract: Real-world decision problems, such as Domestic Hot Water (DHW) production, require the consideration of multiple, possibly conflicting objectives. This work suggests an adaptation of Deep Q-Networks (DQN) to solve multi-objective sequential decision problems using scalarization functions. The adaptation was applied to train multiple agents to control DHW systems in order to find possible trade-offs between comfort and energy cost reduction. Results have shown the possibility of finding multiple policies to meet preferences of different users. Trained agents were tested to ensure hot water production with variable energy prices (peak and off-peak tariffs) for several consumption patterns and they can reduce energy cost from 10.24 % without real impact on users’ comfort and up to 18 % with slight impact on comfort.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Ibrahim, M.; Lecoeuche, S.; Boonaert, J. and Batton-Hubert, M. (2023). Multi-Objective Deep Q-Networks for Domestic Hot Water Systems Control. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-623-1; ISSN 2184-433X, SciTePress, pages 234-242. DOI: 10.5220/0011647400003393

@conference{icaart23,
author={Mohamed{-}Harith Ibrahim. and Stéphane Lecoeuche. and Jacques Boonaert. and Mireille Batton{-}Hubert.},
title={Multi-Objective Deep Q-Networks for Domestic Hot Water Systems Control},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2023},
pages={234-242},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011647400003393},
isbn={978-989-758-623-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Multi-Objective Deep Q-Networks for Domestic Hot Water Systems Control
SN - 978-989-758-623-1
IS - 2184-433X
AU - Ibrahim, M.
AU - Lecoeuche, S.
AU - Boonaert, J.
AU - Batton-Hubert, M.
PY - 2023
SP - 234
EP - 242
DO - 10.5220/0011647400003393
PB - SciTePress

- Science and Technology Publications, Lda.
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