Advancing photovoltaic power forecast accuracy: A hybrid particle filter and recurrent neural network model for data-scarce scenarios toward thermal adaptation

Accurate PV forecasting is vital for grid stability, efficient energy management, and maximizing the use of solar power, especially as solar adoption grows and weather conditions remain unpredictable. This study examines particle filter-enhanced neural networks for photovoltaic power forecasting tow...

Ausführliche Beschreibung

Bibliografische Detailangaben

1. Verfasser:	Mohammed Alghassab
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Elsevier 2025-11-01
Schriftenreihe:	Case Studies in Thermal Engineering
Schlagworte:	Photovoltaic power forecasting Particle filter Renewable energy forecasting Recurrent neural networks Small dataset
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S2214157X25015072
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