Research

Research in computational science with focus on wind energy systems, optimisation formulation, and robust modelling workflows.

PhD - Data Science-Enhanced Wind Power Modelling: From Reanalysis Correction to Energy System Representation

Ongoing

A comprehensive research project for improving wind power modelling through data-driven bias correction and enhanced representation in energy system models.

Geographic variability in reanalysis wind speed biases: A high-resolution bias correction approach for UK wind energy

Published

A spatially granular bias correction method for improving wind resource estimates and energy system planning outcomes.

Open link ↗

Improving wind power modelling through granular spatial and temporal bias correction of reanalysis data

Published

A novel bias correction method for enhancing the accuracy of wind resource assessments and energy system optimization.

Open link ↗

Multi-Output Regression with Generative Adversarial Networks (MOR-GANs)

Published

A novel approach for multi-output regression using generative adversarial networks, enhancing predictive performance in complex systems.

Open link ↗