Enhancing solar power prediction using machine learning: A comparative study of ensemble approaches with explainable AI insights

Solar power prediction is important for effective energy planning and grid stability. However, it is a complex process owing to changing atmospheric conditions and the nonlinear characteristics of photovoltaic (PV) systems. This paper compares the efficacy of various machine learning methods based o...

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Hlavní autoři:	Kehinde Temitope Alao, Kamaruzzaman Sopian, Syed Ihtsham Ul Haq Gilani, Damilare Samuel Oyebamiji, Taiwo Onaopemipo Alao, Zeshan Aslam, Hussein A. Kazem
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Elsevier 2026-07-01
Edice:	Next Energy
Témata:	Solar power prediction Machine learning Ensemble learning Explainable AI SHAP analysis
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S2949821X26002383
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