Advancing solar PV panel power prediction: A comparative machine learning approach in fluctuating environmental conditions

• Main Authors: Tripathi, Abhishek Kumar, Mangalpady, Aruna, Elumalai, P.V., Karthik, Krishnasamy, Khan, Sher Afghan, Asif, Mohammad, Rao, Koppula Srinivas
• Format: Article
• Language: English
• Published: Elsevier Ltd 2024
• Subjects: TJ163.26 Energy conservation
• Online Access: http://irep.iium.edu.my/112174/2/112174_Advancing%20solar%20PV%20panel%20power%20prediction.pdf; http://irep.iium.edu.my/112174/; https://www.sciencedirect.com/science/article/pii/S2214157X24004908/pdfft?md5=7abfe3686998480f7d3783fe557a5b8f&pid=1-s2.0-S2214157X24004908-main.pdf; https://doi.org/10.1016/j.csite.2024.104459

Solar photovoltaic (PV) panels play a crucial role in sustainable energy generation, yet their power output often faces uncertainties due to dynamic weather conditions. In this study, a comparative machine learning approach is introduced, utilizing multivariate regression (MR), support vector machin...