Modelling Solar PV Adoption in Irish Dairy Farms using Agent-Based Modelling

Iias Faiud, Michael Schukat, Karl Mason
1/15/2024
cs.MAphysics.soc-ph

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Abstract

The agricultural sector is facing mounting demands to enhance energy efficiency within farm enterprises, concurrent with a steady escalation in electricity costs. This paper focuses on modelling the adoption rate of photovoltaic (PV) energy within the dairy sector in Ireland. An agent-based modelling approach is introduced to estimate the adoption rate. The model considers grid energy prices, revenue, costs, and maintenance expenses to calculate the probability of PV adoption. The ABM outputs estimate that by year 2022, 2.45% of dairy farmers have installed PV. This is a 0.45% difference to the actual PV adoption rate in year 2022. This validates the proposed ABM. The paper demonstrates the increasing interest in PV systems as evidenced by the rate of adoption, shedding light on the potential advantages of PV energy adoption in agriculture. This study possesses the potential to forecast future rates of PV energy adoption among dairy farmers. It establishes a groundwork for further research on predicting and understanding the factors influencing the adoption of renewable energy.

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Cite this paper

@article{faiud2024modelling,
  title  = {Modelling Solar PV Adoption in Irish Dairy Farms using Agent-Based Modelling},
  author = {Iias Faiud and Michael Schukat and Karl Mason},
  year   = {2024},
  eprint = {2401.16222},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.16222v1}
}

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