A Multi-Agent Systems Approach for Peer-to-Peer Energy Trading in Dairy Farming

TL;DR

This paper introduces MAPDES, a multi-agent simulation framework that enables dairy farms to participate in peer-to-peer energy trading, significantly reducing costs and peak demand while increasing energy sales.

Contribution

The paper presents a novel multi-agent simulation tool for P2P energy trading in dairy farms, demonstrating its effectiveness in cost reduction and increased energy sales.

Findings

Electricity costs reduced by approximately 30%.

Peak demand decreased by about 24%.

Energy sales increased by 37%.

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.