Use of support vector regression and numerically predicted cloudiness to forecast power output of a photovoltaic power plant in Kitakyushu, Japan
By Joao Gari Silva Fonseca, Takashi Oozeki, T. Takashima, G. Koshimizu, Yoshihisa Uchida, Kazuhiko Ogimoto. 2012
152 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/0f452ebe7258d624264bfda5f2590df056168fd1
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In Artificial Intelligence
- F. J. Martínez-de-Pisón
- Fernando Antoñanzas-Torres
- Javier Antoñanzas
- R. Escobar
- Rubén Urraca
- N. Osório
Citations in the corpus
- Review of photovoltaic power forecasting (2016, methodology): “Fonseca et al. (2014c) constructed their regional forecasts based on NWP from the Japan Meteorology Agency for the location of each PV plant and then, performed a PCA to avoid redundant information (i.e. NWP of PV plants located close to each other). It was observed that the proposed methodology, ba”