Economic Trades in Energy Communities and Optimal Allocation
Laura Wangen (laura.wangen@univ-grenoble-alpes.fr) and
Cédric Clastres (cedric.clastres@univ-grenoble-alpes.fr)
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Laura Wangen: GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes
Cédric Clastres: GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes
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Abstract:
The crucial issue on how to model an optimal economic trading model for Energy Communities (ECs) reveals the need for adapted trading mechanisms and pricing strategies in emerging decentralised market forms. Yet, the extent to which these trading models influence the allocation of costs and benefits to EC members remains unexplored. This article provides an overview of existing literature findings, lays down relevant models and derives essential principles for economic trades inside ECs. For this purpose, this article conducts a comprehensive review of relevant literature across economic and engineering domains, with a specific focus on ECs and Peer-to-Peer (P2P) markets. By examining these concepts, important obstacles and enablers of local energy trading are discussed and related to the framework of ECs. Among the assessed models, the community-based P2P model emerges as highly adaptable for ECs, primarily due to its potential to foster cooperation among prosumers. Furthermore, this article delves into vital insights concerning sharing mechanisms and their integration within trading models. Finally, essential conditions and key considerations are proposed to determine the optimal energy trading structure for ECs, including the need to find a balance between efficiency, fairness and scalability in the design of allocation methods.
Keywords: Energy Communities; Local energy trading; Cost allocation designs; Prosumers; Peer-to-Peer Energy Trading; Optimisation models (search for similar items in EconPapers)
Date: 2024-03-27
Note: View the original document on HAL open archive server: https://hal.science/hal-04539585v1
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Published in 2nd Conference on Decentralized Energy Systems, Université de Rouen Normandie (LERN); NEOMA Business School (the World We Want); Paris School of Economics (Urban New Deal chair), Mar 2024, Rouen, France
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