J. M. Morales González, E. Ruiz Irusta
Peer-to-peer energy trading platforms enable direct electricity exchanges between peers who belong to the same energy community. However, with no supervision, some peers can be discriminated against from participating in the electricity trades. To solve this issue, this paper proposes an optimization-based mechanism to enable distributionally fair peer-to-peer electricity trading. For the implementation of our mechanism, peers are grouped by energy poverty level and electricity trades are redistributed to minimize the maximum Wasserstein distance among the transaction distributions linked to the groups while limiting the sacrifice level with a predefined parameter. We demonstrate the effectiveness of our proposal using the IEEE 33-bus distribution grid, simulating an energy community with 1600 peers. Results indicate that up to 70.1% of unfairness can be eliminated by using the proposed model, even achieving a full elimination when including a non-profit community photovoltaic plant.
Keywords: OR in energy, Peer-to-Peer, Fairness, Wasserstein metric
Scheduled
Optimization and Learning in Energy
June 11, 2025 3:30 PM
Auditorio 2. Leandre Cristòfol