Alain Ulazia

Wave Energy Forecasting at Three Coastal Buoys in the Bay of Biscay

In 2008, the first commercial wave farm came online in Portugal. As with other types of renewable energy, the electricity obtained from waves has the drawback of intermittency. Knowing a few hours ahead how much energy waves will hold can contribute to a better management of the electricity grid. In this work, three types of statistical models have been used to create up to 24-h forecasts of the zonal and meridional components of wave energy flux (WEF) levels at three directional buoys located off the coast in the Bay of Biscay. Each models performance has been compared at a 95% confidence level with the simplest prediction (persistence of levels), along with the forecasts provided by the physics-based WAve Modeling (WAM) wave model at the nearest grid point. The results indicate that for forecasting horizons between 3 and roughly 16 h ahead, the statistical models built on random forests (RFs) outperform the rest, including WAM and persistence.

Using open software to teach resource assessment of solar thermal and geothermal energy

The students of the Faculties of Engineering of the Universitty of Basque Country (Gipuzkoa-Eibar) in the last years of their studies, before becoming engineers, have the opportunity to select a block of subjects intended to enhance their knowledge on renewable energy systems. One of these subjects is Solar Thermal and Geothermal energy. These subjects are devoted to assessing the renewable energy resource, and designing optimal systems. Apart from the transmission of good practices, the focus is practical and is based on hands-on computer real-life exercises, which involves not only intensive programming using high-level software, but also the spatial representation of results. To that purpose two main open source codes are used: Octave (https://www.gnu.org/software/octave/), and QGIS (https://www.qgis.org/). Students learn how to address real-life problems regarding the geographical representation of solar radiation and low temperature geothermal resources using QGIS, and solar thermal system modelling using Octave.

Study of ocean and wind energy potential with R: an innovative experience in the classroom

Abstract The Engineer School of Eibar initiated the Grade of Engineering in Renewable Energies four years ago. This pioneering educational project has shown many challenges to the teachers of the new grade. Among the different software skills used in this project, R programming language has been a very important one because of its capacity for spatio-temporal analysis and graphical visualization of wind energy and wave energy potential. A quarter of the subjects program in Wind Energy and Ocean Energy has been used via Problem Based Learning for the application of statistical calculus with R. The aim of this contribution is to show some paradigmatic problems solved by the students and the results obtained. Finally, the opinion of the students about the use of R and its learning potentiality have been gathered and analysed.