Title :
Comparative analysis between wind and solar forecasting methods using artificial neural networks
Author :
Adela B?ra;George C?ru?a?u;Cornelia Botezatu;Alexandru P?rjan
Author_Institution :
The Bucharest University of Economic Studies
Abstract :
This paper presents the architecture and the prediction model component of the research project "Intelligent system for prediction, analysis and monitoring of performance indicators of technological and business processes in the field of renewable energies" (SIPAMER) funded by NASR. The prediction model takes into account the solar and wind power plants´ data and predicts with a high accuracy the energy produced using neural networks.
Keywords :
"Wind forecasting","Production","Photovoltaic systems","Wind power generation"
Conference_Titel :
Computational Intelligence and Informatics (CINTI), 2015 16th IEEE International Symposium on
DOI :
10.1109/CINTI.2015.7382900