Abstract
Local energy communities are identified as a promising approach to efficiently integrate distributed generation whereas keeping costs down for prosumers. In this context, we propose a multi-agent system to collectively optimise the energy flows of a local community of prosumers. The novelty and strength of our approach resides in the use of decentralised decision making algorithms, based on the alternating direction method of multipliers, to orchestrate the demand and supply of a large number of homes. Our preliminary results show how the proposed approach can significantly increase the self-consumption level of the community while significantly reducing the energy bills of its members.
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Acknowledgments
Authors would like to acknowledge the support of the European Union under the FP7 Grant Agreement no. 619682 (MAS2TERING project).
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Vinyals, M., Velay, M., Sisinni, M. (2018). A multi-agent system for energy trading between prosumers. In: Omatu, S., RodrÃguez, S., Villarrubia, G., Faria, P., Sitek, P., Prieto, J. (eds) Distributed Computing and Artificial Intelligence, 14th International Conference. DCAI 2017. Advances in Intelligent Systems and Computing, vol 620. Springer, Cham. https://doi.org/10.1007/978-3-319-62410-5_10
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DOI: https://doi.org/10.1007/978-3-319-62410-5_10
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