Validation of SWAN Model for Wave Energy Resource Analysis

The world energy demand is still increasing, even though the Covid-19 pandemic had a negative effect on the growth. As a result, despite the lower pace, CO2 emissions are still growing. In this scenario, renewable energy sources play a crucial role in empowering the energy transition. Among renewable energy sources, marine energy and in particular sea waves possess a huge potential. The total world potential of wave energy is estimated to be around 29500 TWh/year, more than the current world electricity demand. There is a lot of research going on, as a result the technologies exploiting wave energy are constantly evolving and growing. In order to exploit sea waves energy, the first step is to perform a resource analysis, hence characterizing the sea state. To characterize the sea state in a fixed location, the fundamental parameters are the significant wave height HS, the peak period TP and the mean wave direction ϑm. Time series of the parameters above can be obtained either through direct measurements, or thanks to provisional models. For direct measurements often wave buoys are used, even though they have the defect of being present only in a few locations and for a limited time. It is therefore important to develop models permitting to map the resource availability with good affordability. In this thesis, the sea state data derived from ECMWF and SWAN models are compared to synthetic data obtained from direct measurements, in particular from a RON buoy, positioned near the city Alghero, in Sardinia.