Peer-to-peer energy trading in dairy farms using multi-agent systems.

To accomplish the desired reduction in carbon emissions, society must improve the integration of renewable generation and accelerate the adoption of technologies like peer-to-peer energy trading. This necessity is particularly evident in the agriculture sector, specifically for energy-intensive forms of farming, such as dairy farming. Nevertheless, the integration of renewable energy sources and peer-to-peer energy trading presents notable challenges. Effective control strategies are essential for dairy farms to engage in peer-to-peer energy trading markets. This paper introduces the Multi-Agent Peer-to-Peer Dairy Farm Energy Simulator-extended (MAPDES), which leverages multi-agent systems to facilitate the participation of dairy farms in peer-to-peer markets. The energy trading strategy yields a 43% reduction in electricity costs and a 42% decrease in peak demand, while also increasing energy sales by 59% compared to the baseline scenario, which does not include peer-to-peer energy trading or renewable energy sources. This model has been tested across various farm community sizes, renewable energy combinations, and geographical locations to determine the ideal farm community configuration and assess the model's applicability across different settings. • Developing a Multi-Agent System for Peer-to-Peer Energy Trading in Dairy Farming. • Analyzing case studies of dynamic renewable energy and farm sizes/locations for optimal setup. • Evaluating P2P dairy farm energy trading using case studies from Finland and Ireland. • Evaluating the algorithm's practical use in dairy farming by assessing its efficiency and real-time capabilities. [ABSTRACT FROM AUTHOR]