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A Multi-agent Systems Approach for Peer-to-Peer Energy Trading in Dairy Farming

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Artificial Intelligence. ECAI 2023 International Workshops (ECAI 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1948))

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Abstract

To achieve desired carbon emission reductions, integrating renewable generation and accelerating the adoption of peer-to-peer energy trading is crucial. This is especially important for energy-intensive farming, like dairy farming. However, integrating renewables and peer-to-peer trading presents challenges. To address this, we propose the Multi-Agent Peer-to-Peer Dairy Farm Energy Simulator (MAPDES), enabling dairy farms to participate in peer-to-peer markets. Our strategy reduces electricity costs and peak demand by approximately 30% and 24% respectively, while increasing energy sales by 37% compared to the baseline scenario without P2P trading. This demonstrates the effectiveness of our approach.

Proc. of the Artificial Intelligence for Sustainability, ECAI 2023, Eunika et al. (eds.), Sep 30- Oct 1, 2023, https://sites.google.com/view/ai4s. 2023.

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Acknowledgements

This publication has emanated from research conducted with the financial support of Science Foundation Ireland under Grant number [21/FFP-A/9040].

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Correspondence to Mian Ibad Ali Shah .

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Shah, M.I.A., Wahid, A., Barrett, E., Mason, K. (2024). A Multi-agent Systems Approach for Peer-to-Peer Energy Trading in Dairy Farming. In: Nowaczyk, S., et al. Artificial Intelligence. ECAI 2023 International Workshops. ECAI 2023. Communications in Computer and Information Science, vol 1948. Springer, Cham. https://doi.org/10.1007/978-3-031-50485-3_27

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  • DOI: https://doi.org/10.1007/978-3-031-50485-3_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-50484-6

  • Online ISBN: 978-3-031-50485-3

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