@inproceedings{c43cb93de7e3469bb6a45bd4a7258910,
title = "Evaluating the Impact of Subsidies on Solar PV Adoption Using Multi-Agent Systems and Machine Learning",
abstract = "This study analyzes the impact of subsidies on the adoption of solar photovoltaic (PV) systems in Irish dairy farms using a multi-agent systems model. The model examines the interactions between policymakers and dairy farms, integrating a linear regression model to forecast electricity prices. Our findings demonstrate that higher subsidies significantly boost PV adoption rates, with adoption increasing from 2 \% at a 40 \% subsidy to 20.9 \% at a 7 0 \% subsidy. These results provide valuable insights for policymakers, highlighting the effectiveness of subsidies in promoting renewable energy adoption. This work underscores the potential of subsidy policies to enhance reliance on renewable energy, thereby reducing CO2 emissions and supporting the transition to sustainable energy sources.",
keywords = "Linear regression, Machine Learning, Multi-agent systems, Photovoltaics, Renewable energy",
author = "Iias Faiud and Michael Schukat and Karl Mason",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 6th International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2024 ; Conference date: 19-10-2024 Through 20-10-2024",
year = "2024",
doi = "10.1109/ICCCMLA63077.2024.10871760",
language = "English",
series = "ICCCMLA 2024 - 6th International Conference on Cybernetics, Cognition and Machine Learning Applications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "32--38",
booktitle = "ICCCMLA 2024 - 6th International Conference on Cybernetics, Cognition and Machine Learning Applications",
}
