RT Journal Article
T1 Hybrid Intelligent Modelling in Renewable Energy Sources-Based Microgrid. A Variable Estimation of the Hydrogen Subsystem Oriented to the Energy Management Strategy
A1 Casteleiro Roca, José Luis
A1 Vivas Fernández, Francisco José
A1 Calvo Rolle, José Luis
A1 Andújar Márquez, José Manuel
AB This work deals with the prediction of variables for a hydrogen energy storage systemintegrated into a microgrid. Due to the fact that this kind of system has a nonlinear behaviour,the use of traditional techniques is not accurate enough to generate good models of the system understudy. Then, a hybrid intelligent system, based on clustering and regression techniques, has beendeveloped and implemented to predict the power, the hydrogen level and the hydrogen systemdegradation. In this research, a hybrid intelligent model was created and validated over a datasetfrom a lab-size migrogrid. The achieved results show a better performance than other well-knownclassical regression methods, allowing us to predict the hydrogen consumption/generation with amean absolute error of 0.63% with the test dataset respect to the maximum power of the system.
PB MDPI
SN 2071-1050
YR 2020
FD 2020-12
LK http://hdl.handle.net/10272/19476
UL http://hdl.handle.net/10272/19476
LA eng
NO Casteleiro Roca, J. L., Vivas Fernández, F. J., Calvo Rolle, J. L. ... Andújar  Márquez, J. M. (2020). Hybrid Intelligent Modelling in Renewable Energy Sources-Based Microgrid. A Variable Estimation of the Hydrogen Subsystem Oriented to the Energy Management Strategy. Sustainability, 12(24), 10566. DOI: https://doi.org/10.3390/su122410566
DS Repositorio Institucional de la Universidad de Huelva
RD 1 jun 2026