Energy efficiency & renewable energy: renewable and sustainable energy
Mentor: Sancho Salcedo Sanz
Email: sancho.salcedo@uah.es
Phone: (+34) 918856731
University: Universidad de Alcalá
Partner Host Institution:
Keywords: Machine Learning; Soft-Computing; Complex Networks; Renewable Energy; Climate; Climate Change;

Energy efficiency & renewable energy: renewable and sustainable energy

The main research line of the group is Machine Learning approaches for analyzing and designing Renewable Energy systems, including Wind, Solar and Marine Energy Systems. We also consider problems of Climatology and Climate Change effects in Renewable Energy Systems, using Machine Learning algorithms and computational techniques.

Departament: Signal Theory and Communications
Research Group: GHEODE
More Information: https://www.uah.es/es/investigacion/unidades-de-investigacion/grupos-de-investigacion/Heuristicos-Modernos-de-Optimizacion-y-Diseno-de-Redes-de-Comunicaciones/
http://agamenon.tsc.uah.es/Personales/sancho/
Relevants projects on the area: New hybrid algorithms of natural inspiration for problems of ordinal classification and prediction.
Relevants publications on the area: 1.- S. Salcedo-Sanz, “Modern meta-heuristics based on nonlinear physics processes: A review of models and design procedures,” Physics Reports, vol. 655, pp. 1-70, 2016. (JCR: 17.425, Q1)
2.- S. Salcedo-Sanz, R. C. Deo, L. Cornejo-Bueno, C. Camacho-Gómez and S. Ghimire, “An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in Sunshine State of Australia,” Applied Energy, vol. 209, pp. 79-94, 2018. (JCR: 7.182, Q1)