# Incentivizing Energy Trading for Interconnected Microgrids

arXiv: https://arxiv.org/abs/1609.07576 · HTML: https://mlsanity.com/paper/1609.07576/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Sep 2016.

## Built on by (most cited first, 7 of 7)

- [Proximal Policy Optimization Based Reinforcement Learning for Joint Bidding in Energy and Frequency Regulation Markets](https://mlsanity.com/paper/2212.06551/) (2022)
- [Dynamic Rolling Horizon Optimization for Network-Constrained V2X Value Stacking of Electric Vehicles Under Uncertainties](https://mlsanity.com/paper/2502.09290/) (2025)
- [Personalized Federated Hypernetworks for Privacy Preservation in Multi-Task Reinforcement Learning](https://mlsanity.com/paper/2210.06820/) (2022)
- [Large Language Model-Assisted Planning of Electric Vehicle Charging Infrastructure with Real-World Case Study](https://mlsanity.com/paper/2511.19055/) (2025)
- [LOOP-MAC: Learning-Based Multi-Agent Coordination with Guaranteed Local Feasibility in a Virtual Power Plant](https://mlsanity.com/paper/2310.17882/) (2023)
- [A Hierarchical MARL-Based Approach for Coordinated Retail P2P Trading and Wholesale Market Participation of DERs](https://mlsanity.com/paper/2604.20586/) (2026)
- [Incentive-Aligned Vehicle-to-Vehicle Energy Trading via Nash-Integrated Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2605.22363/) (2026)

## Abstract (arXiv)

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.