Energies, Journal Year: 2025, Volume and Issue: 18(8), P. 2108 - 2108

Published: April 19, 2025

The fast growth of photovoltaic (PV) power generation requires dependable forecasting methods to support efficient integration solar energy into systems. This study conducts an up-to-date, systematized analysis different models and used for prediction. It begins with a new taxonomy, classifying PV according the time horizon, architecture, selection criteria matched certain application areas. An overview most popular heterogeneous techniques, including physical models, statistical methodologies, machine learning algorithms, hybrid approaches, is provided; their respective advantages disadvantages are put perspective based on tasks. paper also explores advanced model optimization methodologies; achieving hyperparameter tuning; feature selection, use evolutionary swarm intelligence which have shown promise in enhancing accuracy efficiency models. review includes detailed examination performance metrics frameworks, as well consequences weather conditions affecting renewable operational economic implications performance. highlights recent advancements field, deep architectures, incorporation diverse data sources, development real-time on-demand solutions. Finally, this identifies key challenges future research directions, emphasizing need improved adaptability, quality, computational large-scale By providing holistic critical assessment landscape, aims serve valuable resource researchers, practitioners, decision makers working towards sustainable reliable deployment worldwide.

Language: Английский