Abstract:

Marine Energy has been taught for the first time in the University of Basque Country, as a subject within the last course of the innovative Grade in Engineering of Renewable Energies. in Eibar. In this exposition we want to explain how we have dealt with this pioneering challenge by means of the programming language R.

R is a powerful language that is mainly used for statistical and graphical analysis and we have applied it in the spatio-temporal analysis of marine energetic recourse. For example, the potential of wave energy, and temperature or salinity gradient, have been visualized in several maps in our classroom. Or the students have drawn statistical graphics with the application of risk theory to high waves. They have used different satellite data for that such as TOPEX or ETOPO3.

We have taught to two groups of 20 students each. Each student has got his computer and self-learning have been introduced to write by blocks the large scripts needed to solve the presented problems. In this sense, we can say that learning by problems method has been applied in the class. The needed theoretical background and the specific knowledge about the programming language have been introduced as the problems went along in their solving process. Thus, all the knowledge exposition has been contextualized in each step of the didactic process. This practical perspective makes our didactic project an example of integration of classroom and laboratory, in which the real work developed by scientists that calculate the marine potential is simulated in situ. The satellite data collection, searching process and download is a good case in point, since our students search for information in the most sophisticated websites of NASA or NOOA.

It is clear that R is a rich recourse to evaluate and treat spatio-temporal data, since it accumulates a great number of packages of scientists of very different domains.

For example we have used:
- sp package to import raster geographic data and manipulate it as vectorial data.
- maps and mapdata packages to plot shorelines, rivers o political boundaries in low resolution.
- marmap package to plot bathymetric isolines and transects to calculate the depth of the sea
- ismev and evir to fit Gumbel distributions in extreme events such as very high waves.
- etc.

The interdisciplinary knowledge needed to evaluate marine energy (oceanography, treatment of bathymetric data, spatio-temporal statistics, geographical information systems, etc.) offers the possibility to combine many packages working and learning in a very efficient way. Although we have developed problems about wave energy and temperature gradient potential, we can even do the same for salinity gradient or offshore wind energy potential. What is more, we could use analogs or genetic algorithms to forecast in the future the available energy in a considered area of the sea. All these aspects of R offer an interesting instrument for problem solving, self-learning and learning by problems methods.

Keywords:

Marine Energy, R programming language, spatio-temporal analisis.