Background and activities

I am a PhD candidate at the Department of Electric Power Engineering under the supervision of Prof. Elisabetta Tedeschi and financed by FME NothWind.

FME NothWind is the newly established Norwegian Research Centre on Wind Energy led by SINTEF, with research partners NTNU, UiO, NINA and NGI. The primary objective is to bring forward outstanding research and innovation to reduce the cost of wind power and facilitate its sustainable development.

Research Area

My PhD project aims to provide grid services to/from offshore wind farms by means of the integration of energy storage into the HVDC transmission or offshore collection network, increasing the efficiency and robustness of the farm operation. The project faces the following challenges:

  • Find the most suitable energy storage technology to provide ancillary services to HVDC grid, the possible locations depending on the storage philosophy (centralized or distributed) and the sizing of such technology.
  • Identify the needs of current offshore wind farms in order to design an optimal and robust control strategy to support it with ancillary services by means of energy storage.
  • Design an efficient power converter control for the energy storage, which provides security and flexibility to the system.

My research interest includes: ancillary services, HVDC power system robustness, integration of renewable energy in the electric system, offshore wind energy.

Academic Background

  • 2014-2018
    • BSc in Renewable Energy: University of Basque Country (UPV/EHU) – Eibar.
    • Graduation project: Novel Method for the Identification of Defective Anemometers in Wind Farms.
  • 2018-2019
    • MSc in Integration of Renewable Energy in the Electric System: University of Basque Country (UPV/EHU) – Bilbao.
    • Master thesis: Ampacity prediction via artificial neural network and weather forecast. Case study of the medium voltage overhead power line in Elgoibar.
  • 2019-2021


Rabanal, A., Ulazia, A., Ibarra-Berastegi, G., Sáenz, J., & Elosegui, U. (2019). MIDAS: A benchmarking multi-criteria method for the identification of defective anemometers in wind farms. Energies, 12(1), 28.

Ulazia, A., Penalba, M., Rabanal, A., Ibarra-Berastegi, G., Ringwood, J., & Sáenz, J. (2018). Historical evolution of the wave resource and energy production off the Chilean Coast over the 20th Century. Energies, 11(9), 2289.

Ulazia, A., Ibarra, G., Sáenz, J., Rabanal, A., Elosegui, U., & Egaña, I. (2018, October). Novel Method for the Identification of Defective Anemometers in Wind Farms. In 2018 7th International Conference on Renewable Energy Research and Applications (ICRERA) (pp. 819-823). IEEE.