DIGITAL LIBRARY
USING OPEN SOFTWARE TO TEACH RESOURCE ASSESSMENT OF RENEWABLE ENERGIES
University of the Basque Country UPV/EHU (SPAIN)
About this paper:
Appears in: EDULEARN17 Proceedings
Publication year: 2017
Pages: 9198-9204
ISBN: 978-84-697-3777-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2017.0725
Conference name: 9th International Conference on Education and New Learning Technologies
Dates: 3-5 July, 2017
Location: Barcelona, Spain
Abstract:
The University of the Basque Country (http://www.ehu.es) is the most important University in the Autonomous Region of the Basque Country, Spain. There is one degree in Renewable Energy Engineering given at the Gipuzkoa Faculty of Engineering (Eibar). In the last years of their studies, before becoming engineers, students have the opportunity to select a block of subjects intended to enhance their knowledge on Wind Energy, Ocean Energy, Biomass, Hydraulic Energy,Solar Thermal Energy, and Geothermal Energy.

These subjects are devoted to different aspects of the water cycle management, and geographical representations of wind, ocean, biomass, solar and geothermal energy resource. 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 three main open source codes are used: QGIS (https://www.qgis.org/), R (https://www.cran.r-project.org/) and Octave (https://www.gnu.org/software/octave/). Students learn how to address real-life problems regarding geographical representation of wind and ocean energy resource with R, spatial representation of biomass, solar and geothermal resource with QGIS, and solar thermal system modelling using Octave.

The combination of learning by problems and learning by projects techniques, with publicly available databases, and the use of free software enhance the understanding of the problems associated with these energy resources, together with more freedom to improve self-learning.
Keywords:
QGIS, R, Octave, learning by problems, learning by projects.