A Multi-Agent Systems Approach for Peer-to-Peer Energy Trading in Dairy Farming
Mian Ibad Ali Shah, Abdul Wahid, Enda Barrett, Karl Mason
TL;DR
The paper addresses the energy-intensity and emissions challenges in dairy farming by integrating renewable generation with peer-to-peer energy trading using a multi-agent system. It introduces MAPDES, a MAS-based simulator with auction-based market clearing and SDR-driven ISP/IBP pricing to optimize local energy exchanges. Key findings show that combining RE with P2P trading reduces grid energy purchases by about 30%, lowers peak grid demand by about 24%, and increases energy sales by roughly 37% compared to non-P2P scenarios. The work demonstrates a scalable, transparent framework for dairy farm microgrids and points to MARL as a path to further refine market dynamics and decision-making.
Abstract
To achieve desired carbon emission reductions, integrating renewable generation and accelerating the adoption of peer-to-peer energy trading is crucial. This is especially important for energy-intensive farming, like dairy farming. However, integrating renewables and peer-to-peer trading presents challenges. To address this, we propose the Multi-Agent Peer-to-Peer Dairy Farm Energy Simulator (MAPDES), enabling dairy farms to participate in peer-to-peer markets. Our strategy reduces electricity costs and peak demand by approximately 30% and 24% respectively, while increasing energy sales by 37% compared to the baseline scenario without P2P trading. This demonstrates the effectiveness of our approach.