Forecasting photovoltaic production with neural networks and weather features

In this paper, we address the refinement of solar energy forecasting within a 2-day window by integrating weather forecast data and strategically employing entity embedding, with a specific focus on the Multilayer Perceptron (MLP) algorithm. Through the analysis of two years of hourly solar energy p...

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Veröffentlicht in:	Energy economics 2024-11, Vol.139, p.107884, Article 107884
Hauptverfasser:	Goutte, Stéphane, Klotzner, Klemens, Le, Hoang-Viet, von Mettenheim, Hans-Jörg
Format:	Artikel
Sprache:	eng
Schlagworte:	Entity embedding Machine learning Neural networks Quantitative Finance Solar energy Time series forecasting
Online-Zugang:	Volltext
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