Mahmoud Elsanhoury, Caner Çuhac , Janne Koljonen , Mohammed Elmusrati
A huge source of energy lies within the incident solar heat and light from the sun, especially for colder territories found in the Nordics such as Finland. For a country situated with close proximity to the North pole, Finland suffers from chilling conditions most of the year in addition to the withheld Sun light. Except during the very short seasons of spring and summer when the Sun remains in the sky for almost 22 hours per day on average. Thus, solar heat flux and solar irradiation become essential energy sources between April and September annually. However, solar irradiance is a physical quantity that is highly affected by probabilistic uncertainty found in many weather conditions, solar behavior throughout the year, time of the day, and the geographical location. In this article, we propose a solar irradiance estimation method base on the Extended Kalman algorithms. The experiment was carried out between the years 2014-2016 in which we installed solar radiation sensors underground and on a rooftop inside the campus of Vaasa University. The readings were collected via an embedded system specifically designed for the endeavors of this experiment. The results showed that the algorithm was able to predict the incident solar irradiance on the city of Vaasa (Finland) with an acceptable accuracy range.