Day-Ahead Photovoltaic Power Forecasting Using Empirical Mode Decomposition Based on Similarity-Day Extension Without Information Leakage
Author:
Funder
Chongqing University of Technology
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
https://link.springer.com/content/pdf/10.1007/s13369-023-08534-w.pdf
Reference53 articles.
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2. Pietrosemoli, L.; Rodríguez-Monroy, C.: The Venezuelan energy crisis: renewable energies in the transition towards sustainability. Renew. Sustain. Energy Rev. 105, 415–426 (2019). https://doi.org/10.1016/j.rser.2019.02.014
3. Antonanzas, J.; Osorio, N.; Escobar, R.; Urraca, R.; Martinez-de-Pison, F.J.; Antonanzas-Torres, F.: Review of photovoltaic power forecasting. Sol. Energy 136, 78–111 (2016). https://doi.org/10.1016/j.solener.2016.06.069
4. Edenhofer, O.; Pichs Madruga, R.; Sokona, Y.: United Nations Environment Programme, World Meteorological Organization, Intergovernmental Panel on Climate Change, Potsdam-Institut für Klimafolgenforschung eds: Renewable Energy Sources and Climate Change Mitigation: Special Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, New York (2012)
5. Iheanetu, K.J.: Solar photovoltaic power forecasting: a review. Sustainability 14, 17005 (2022). https://doi.org/10.3390/su142417005
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