Incentivizing Peer-to-Peer Energy Trading in Microgrids

TL;DR

This paper proposes a distributed peer-to-peer energy trading mechanism in microgrids that incentivizes prosumers, optimizes social welfare, and improves cost fairness through a continuous double auction and adaptive algorithms.

Contribution

It introduces a novel distributed adaptive algorithm for P2P energy trading in microgrids based on continuous double auction, enhancing fairness and efficiency.

Findings

The proposed method incentivizes P2P energy trading.

It improves cost fairness among prosumers.

It reduces peak-to-average ratio in microgrid operation.

Abstract

Recent trends express the impact of prosumers and small energy resources and storages in distribution systems, due to the increasing uptake of renewable resources. This research studies the effect of coordination of distributed resources with the utility grid and the role of prosumers in the operation of renewable microgrids. We formulated this problem as a social welfare maximization problem followed by employing the dual decomposition method to decompose it into sub-problems of the microgrid, distributed generators, prosumers, and consumers. Moreover, the corresponding power balance mechanism via price adjustment can be viewed as a Walrasian tatonnement process. Specifically, prosumers and consumers compete to adjust their energy exchange with other agents to maximize their profit gained by renewable emission reduction benefits while minimizing the associated cost of energy. To this end, we have adopted a peer-to-peer energy trading mechanism based on continuous double auction that can be viewed as a multi-parametric quadratic problem. Finally, we proposed a distributed adaptive algorithm that determines strategies as well as payment and assignment rules. The numerical result suggests that the proposed method can incentivize peer-to-peer energy trading while improving the cost fairness problem and the peak-to-average ratio.