# Modelling Electricity Consumption in Irish Dairy Farms Using Agent-Based Modelling

arXiv: https://arxiv.org/abs/2308.09488 · HTML: https://mlsanity.com/paper/2308.09488/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 12 references that are in the map.
- First posted on arXiv 18 Aug 2023.

## Builds on (most cited first, 1 of 1)

- [Modelling Electricity Consumption in Office Buildings: An Agent Based Approach](https://mlsanity.com/paper/1305.7437/) (2013)

## Built on by (most cited first, 3 of 3)

- [A Reinforcement Learning Approach to Dairy Farm Battery Management using Q Learning](https://mlsanity.com/paper/2403.09499/) (2024)
- [Reinforcement Learning Enabled Peer-to-Peer Energy Trading for Dairy Farms](https://mlsanity.com/paper/2405.12716/) (2024)
- [Forecast Aware Deep Reinforcement Learning for Efficient Electricity Load Scheduling in Dairy Farms](https://mlsanity.com/paper/2601.08052/) (2026)

## Abstract (arXiv)

Dairy farming can be an energy intensive form of farming. Understanding the factors affecting electricity consumption on dairy farms is crucial for farm owners and energy providers. In order to accurately estimate electricity demands in dairy farms, it is necessary to develop a model. In this research paper, an agent-based model is proposed to model the electricity consumption of Irish dairy farms. The model takes into account various factors that affect the energy consumption of dairy farms, including herd size, number of milking machines, and time of year. The outputs are validated using existing state-of-the-art dairy farm modelling frameworks. The proposed agent-based model is fully explainable, which is an advantage over other Artificial Intelligence techniques, e.g. deep learning.