Regional forecasts and smoothing effect of photovoltaic power generation in Japan: An approach with principal component analysis
By João Gari da Silva Fonseca Junior, Takashi Oozeki, Hideaki Ohtake, Ken-ichi Shimose, T. Takashima, Kazuhiko Ogimoto. 2014
60 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/83f2d81926af4b5d6fd962787e3c9494efbd9481
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- F. J. Martínez-de-Pisón
- Fernando Antoñanzas-Torres
- Javier Antoñanzas
- R. Escobar
- Rubén Urraca
- Cyril Voyant
- N. Osório
- Marie-Laure Nivet
In Electrical and Electronic Engineering
In Renewable Energy, Sustainability and the Environment
Citations in the corpus
- Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting (2018, methodology): “A solution consists in using local storage in combination 160 with ISRES in order to compensate deviations between forecasted and produced electricity [18161 19,22,31] or in combining several ISRES spread over a large area in such a way that individual 162 prediction errors of each ISRES are indepen”
- Grid Integration Challenges and Solution Strategies for Solar PV Systems: A Review (2022, background): “Many advanced technologies, including geographical dispersion [228], principal component analysis [229], fuzzy”
- Review of photovoltaic power forecasting (2016, methodology): “Two of the methods, summing individual forecasts (M1) and directly forecasting regional PV (PCA approach) (M3) had already been introduced in former articles and two new ones were proposed.”