Explicit Reward Mechanisms for Local Flexibility in Renewable Energy Communities
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866918279249920000 |
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| author | Stegen, Thomas Allard, Julien Diffels, Noé Vallée, François Glavic, Mevludin De Grève, Zacharie Cornélusse, Bertrand |
| author_facet | Stegen, Thomas Allard, Julien Diffels, Noé Vallée, François Glavic, Mevludin De Grève, Zacharie Cornélusse, Bertrand |
| contents | Incentivizing flexible consumption of end-users is key to maximizing the value of local exchanges within Renewable Energy Communities. If centralized coordination for flexible resources planning raises concerns regarding data privacy and fair benefits distribution, state-of-the-art approaches (e.g., bi-level, ADMM) often face computational complexity and convexity challenges, limiting the precision of embedded flexible models. This work proposes an iterative resolution procedure to solve the decentralized flexibility planning with a central operator as a coordinator within a community. The community operator asks for upward or downward flexibility depending on the global needs, while members can individually react with an offer for flexible capacity. This approach ensures individual optimality while converging towards a global optimum, as validated on a 20-member domestic case study for which the gap in terms of collective bill is not more than 3.5% between the decentralized and centralized coordination schemes. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2601_05756 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Explicit Reward Mechanisms for Local Flexibility in Renewable Energy Communities Stegen, Thomas Allard, Julien Diffels, Noé Vallée, François Glavic, Mevludin De Grève, Zacharie Cornélusse, Bertrand Systems and Control Computational Engineering, Finance, and Science Incentivizing flexible consumption of end-users is key to maximizing the value of local exchanges within Renewable Energy Communities. If centralized coordination for flexible resources planning raises concerns regarding data privacy and fair benefits distribution, state-of-the-art approaches (e.g., bi-level, ADMM) often face computational complexity and convexity challenges, limiting the precision of embedded flexible models. This work proposes an iterative resolution procedure to solve the decentralized flexibility planning with a central operator as a coordinator within a community. The community operator asks for upward or downward flexibility depending on the global needs, while members can individually react with an offer for flexible capacity. This approach ensures individual optimality while converging towards a global optimum, as validated on a 20-member domestic case study for which the gap in terms of collective bill is not more than 3.5% between the decentralized and centralized coordination schemes. |
| title | Explicit Reward Mechanisms for Local Flexibility in Renewable Energy Communities |
| topic | Systems and Control Computational Engineering, Finance, and Science |
| url | https://arxiv.org/abs/2601.05756 |