The renewable energies are increasingly earning its share in the energetic outlook, even getting at times bigger stakes than traditional energy sources, such as fossil and nuclear, e.g. in Portugal during 2013 there were some days of 100% renewable energy output. With its increasingly demand for energy, humanity needs to invest in this type of power sources and solar power is potentially the biggest one we have access to.

 

In the present thesis a forecasting method for photovoltaic micro-generation is developed using forecasting up to 72 hours ahead using Extreme Learning Machines (ELM) which allows non-linear between power production and numerical weather predictions (NWP). The data used is from a real source located in southern Italy, having, therefore, a similar latitude to Portugal.