Incentivizing Energy Trading for Interconnected Microgrids

TL;DR

This paper proposes a decentralized energy trading and scheduling strategy for interconnected microgrids, using Nash bargaining to incentivize fair cooperation and significantly reduce operational costs.

Contribution

It introduces a novel incentive mechanism based on Nash bargaining for microgrid energy trading, with a practical decentralized implementation and demonstrated cost savings.

Findings

Total cost reduced by up to 13.2% through trading.

Individual microgrid costs reduced by up to 29.4%.

Decentralized solution minimizes information exchange overhead.

Abstract

In this paper, we study the interactions among interconnected autonomous microgrids, and propose a joint energy trading and scheduling strategy. Each interconnected microgrid not only schedules its local power supply and demand, but also trades energy with other microgrids in a distribution network. Specifically, microgrids with excessive renewable generations can trade with other microgrids in deficit of power supplies for mutual benefits. Since interconnected microgrids operate autonomously, they aim to optimize their own performance and expect to gain benefits through energy trading. We design an incentive mechanism using Nash bargaining theory to encourage proactive energy trading and fair benefit sharing. We solve the bargaining problem by decomposing it into two sequential problems on social cost minimization and trading benefit sharing, respectively. For practical implementation, we propose a decentralized solution method with minimum information exchange overhead. Numerical studies based on realistic data demonstrate that the total cost of the interconnected-microgrids operation can be reduced by up to 13.2% through energy trading, and an individual participating microgrid can achieve up to 29.4% reduction in its cost through energy trading.