An agent-based modeling approach for simulating solar PV adoption: A case study of Irish dairy farms

• Published in: Renewable energy focus 2024-10, Vol.51, p.100653, Article 100653
• Main Authors: Faiud, Iias, Schukat, Michael, Mason, Karl
• Format: Article
• Language: English
• Subjects: Agent-based modeling; Decision-making; Photovoltaics; Renewable energy; Sustainability
• ISSN: 1755-0084
• DOI: 10.1016/j.ref.2024.100653

The agricultural sector faces increasing pressure to enhance energy efficiency in light of escalating electricity costs. This study aims to simulate the adoption of photovoltaic (PV) systems in Ireland’s dairy sector using an agent-based modeling (ABM) approach to facilitate PV uptake among dairy farmers. The model incorporates factors such as grid energy costs, annual electricity consumption, annual solar generation, PV cost, and maintenance expenses to predict PV adoption likelihood. Findings reveal that by 2022, about 2.41% of Irish dairy farmers had adopted PV systems, a figure only 0.41 pp higher than the actual observed rate, validating the ABM’s accuracy. Additionally, the research forecasts future adoption rates of PV systems among dairy farmers, demonstrating the efficacy of ABM in understanding and predicting renewable energy uptake in the dairy sector. These insights can inform policy suggestions to promote renewable energy adoption, ultimately enhancing energy efficiency and sustainability in dairy sector. •Develop an agent-based model of solar PV adoption for the dairy farming sector.•Validate the model by simulating solar PV adoption in Ireland’s dairy sector.•Predict future PV adoption rates through various scenarios.