A New Long-Term Photovoltaic Power Forecasting Model Based on Stacking Generalization Methodology

In recent times, solar energy has become a highly promising source of energy and one of the most regular types of sustainable energy. Forecasting the availability of solar energy has become a concern of many studies because of the intermittent characteristics of solar power. This study proposes a ne...

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Veröffentlicht in:	Natural resources research (New York, N.Y.) Jg. 31; H. 3; S. 1265 - 1287
Hauptverfasser:	Ofori-Ntow Jnr, Eric, Ziggah, Yao Yevenyo, Rodrigues, Maria Joao, Relvas, Susana
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.06.2022 Springer Nature B.V
Schlagworte:	Artificial neural networks Back propagation networks Bayesian analysis Chemistry and Earth Sciences Computer Science Earth and Environmental Science Earth Sciences Energy sources Errors Forecasting Fossil Fuels (incl. Carbon Capture) Geography Group method of data handling Mathematical Modeling and Industrial Mathematics Mathematical models Methodology Mineral Resources Neural networks Original Paper Photovoltaics Physics Radial basis function Solar energy Solar power Statistics for Engineering Support vector machines Sustainable Development Sustainable energy Long-term forecasting Photovoltaic power Stacked generalization methodology Solar energy
ISSN:	1520-7439, 1573-8981
Online-Zugang:	Volltext
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