Computational science
Wind energy systems, reanalysis bias correction, and the integration of physical modelling into continental-scale energy system optimisation.
A comprehensive research project for improving wind power modelling through data-driven bias correction and enhanced representation in energy system models.
A spatially granular bias correction method for improving wind resource estimates and energy system planning outcomes.
A novel bias correction method for enhancing the accuracy of wind resource assessments and energy system optimization.
A novel approach for multi-output regression using generative adversarial networks, enhancing predictive performance in complex systems.