RT info:eu-repo/semantics/article
T1 A Hybrid Intelligent System to forecast solar energy production
A1 Basurto Hornillos, Nuño
A1 Arroyo Puente, Ángel
A1 Vega, Rafael
A1 Quintián, Héctor
A1 Calvo-Rolle, José Luis
A1 Herrero Cosío, Álvaro
K1 Hybrid Intelligent System
K1 Clustering
K1 Regression
K1 Neural networks
K1 Solar Energy
K1 Renewable energies
K1 Informática
K1 Computer science
AB There is wide acknowledgement that solar energy is a promising and renewable source of electricity.However, complementary sources are sometimes required, due to its limited capacity, in order to satisfy user demand. A Hybrid Intelligent System (HIS) is proposed in this paper to optimize the range of possible solar energy and power grid combinations. It is designed to predict the energy generated by any given solar thermal system. To do so, the novel HIS is based on local models that implement both supervised learning (artificial neural networks) and unsupervised learning (clustering). These techniques are combined and applied to a realworld installation located in Spain. Alternative models are compared and validated in this case study with data from a whole year. With an optimum parameter fit, the proposed system managed to calculate the solar energyproduced by the panel with an error that was lower than 10-4 in 86% of cases.
PB Elsevier
SN 0045-7906
YR 2019
FD 2019-09
LK http://hdl.handle.net/10259/8246
UL http://hdl.handle.net/10259/8246
LA eng
DS Repositorio Institucional de la Universidad de Burgos
RD 09-may-2024