Fair Energy Allocation in Risk-aware Energy Communities

TL;DR

This paper presents a decentralized game-theoretic mechanism for fair and efficient renewable energy allocation in energy communities, accounting for consumer risk attitudes and outperforming naive sharing policies.

Contribution

It introduces a novel non-cooperative game model with a decentralized algorithm for energy sharing, deriving equilibrium strategies and analyzing social cost impacts.

Findings

Nash equilibrium existence and closed-form demand expressions

Decentralized algorithm effectively finds equilibrium strategies

Proposed policy reduces social cost compared to naive sharing

Abstract

This work introduces a decentralized mechanism for the fair and efficient allocation of limited renewable energy sources among consumers in an energy community. In the proposed non-cooperative game, the self-interested community members independently decide whether to compete or not for access to RESs during peak hours and shift their loads analogously. In the peak hours, a proportional allocation (PA) policy is used to allocate the limited RESs among the competitors. The existence of a Nash equilibrium (NE) or dominant strategies in this non-cooperative game is shown, and closed-form expressions of the renewable energy demand and social cost are derived. Moreover, a decentralized algorithm for choosing consumers' strategies that lie on NE states is designed. The work shows that the risk attitude of the consumers can have a significant impact on the deviation of the induced social cost from the optimal. Besides, the proposed decentralized mechanism with the PA policy is shown to attain a much lower social cost than one using the naive equal sharing policy.