Distributionally Fair Peer-to-Peer Electricity Trading

Peer-to-peer energy trading platforms enable direct electricity exchanges between
peers who belong to the same energy community. In a semi-decentralized
system, a community manager adheres to grid restrictions while optimizing
social welfare. However, with no further 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. The proposed model
aims to redistribute the electricity trades 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 our proposed model, even achieving
a full elimination when including a non-profit community photovoltaic plant.