Reinforcement Learning Enabled Peer-to-Peer Energy Trading for Dairy Farms
On the map: Deep reinforcement learning methods → RL for energy, networks and operations
Abstract (arXiv)
Farm businesses are increasingly adopting renewables to enhance energy efficiency and reduce reliance on fossil fuels and the grid. This shift aims to decrease dairy farms' dependence on traditional electricity grids by enabling the sale of surplus renewable energy in Peer-to-Peer markets. However, the dynamic nature of farm communities poses challenges, requiring specialized algorithms for P2P energy trading. To address this, the Multi-Agent Peer-to-Peer Dairy Farm Energy Simulator (MAPDES) has been developed, providing a platform to experiment with Reinforcement Learning techniques. The simulations demonstrate significant cost savings, including a 43% reduction in electricity expenses, a 42% decrease in peak demand, and a 1.91% increase in energy sales compared to baseline scenarios lacking peer-to-peer energy trading or renewable energy sources.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in RL for energy, networks and operations, one of 15 directions in Deep reinforcement learning methods. Builds on 5 of its 33 references that are in the map. First posted on arXiv 21 May 2024.
Builds on
5 of 33 references.
References · 5
- 2018On Cognitive Preferences and the Plausibility of Rule-based Modelscited by 14
- 2022Scalable multi-agent reinforcement learning for distributed control of residential energy flexibilitycited by 11
- 2021Decentralized Microgrid Energy Management: A Multi-agent Correlated Q-learning Approachcited by 5
- 2023Modelling Electricity Consumption in Irish Dairy Farms Using Agent-Based Modellingcited by 3
- 2023A Multi-Agent Systems Approach for Peer-to-Peer Energy Trading in Dairy Farmingcited by 1
Built on by
Citing papers per year: 2025: 3.
3 papers.
- 2025Scalable Fairness Shaping with LLM-Guided Multi-Agent Reinforcement Learning for Peer-to-Peer Electricity Marketscited by 1
- 2025FairMarket-RL: LLM-Guided Fairness Shaping for Multi-Agent Reinforcement Learning in Peer-to-Peer Marketscited by 0
- 2025Uncertainty-Aware Knowledge Transformers for Peer-to-Peer Energy Trading with Multi-Agent Reinforcement Learningcited by 0
- 2025Scalable Fairness Shaping with LLM-Guided Multi-Agent Reinforcement Learning for Peer-to-Peer Electricity Markets26 Aug 2025
- 2025Uncertainty-Aware Knowledge Transformers for Peer-to-Peer Energy Trading with Multi-Agent Reinforcement Learning22 Jul 2025
- 2025FairMarket-RL: LLM-Guided Fairness Shaping for Multi-Agent Reinforcement Learning in Peer-to-Peer Markets28 Jun 2025
Similar, not cited
Close in wording, no citation either way
- 2025Peer-to-Peer Energy Trading in Dairy Farms using Multi-Agent Reinforcement Learning
- 2024Peer-to-Peer Energy Trading of Solar and Energy Storage: A Networked Multiagent Reinforcement Learning Approach
- 2024A Reinforcement Learning Approach to Dairy Farm Battery Management using Q Learning
- 2024A Deep Reinforcement Learning Approach to Battery Management in Dairy Farming via Proximal Policy Optimization
- 2026Multi-Agent Deep Reinforcement Learning for Multi Objective Battery Management in Dairy Farms
- 2025LLM-Enhanced Multi-Agent Reinforcement Learning with Expert Workflow for Real-Time P2P Energy Trading
- 2026Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets
- 2024FRESCO: Federated Reinforcement Energy System for Cooperative Optimization