A fuzzy logic model of a tracking system for solar panels in northern Jordan based on experimental data

Renewable energy is the energy that comes from natural resources and it is the energy that naturally replenished and can be converted from a form to another to be useful for human usage. Solar energy is one form of renewable energy that can be obtained from sun through the form of solar radiation. It is a promising alternative technology that will help to replace petroleum energy sources. However, there are many problems to use such as technology which limits the produced energy. The major problem is the poor efficiency of solar cells and the high cost. Tracking systems are used to maximize electricity output of solar cells. However, this is not a naive task due to the difficulty in finding a general rule that can be used to get optimal output of solar cells for all situations. Moreover, different environments may affect the output of solar cells. Artificial Intelligence could be used to control these parameters for better efficiency. So; the aim of this paper is to introduce an efficient tracking model for the solar panel set that maximizes the energy output of the solar system in the area of Jordan and its neighbors based on practical experiment. The proposed fuzzy model was experimentally evaluated to demonstrate that this system can successfully predict the correct angles with superior results when it provides any average low error rate of 3.55% for predicted tilt angles and 4.1% degrees for predicted orientation angles. This low predicted error indicates that the system can be used efficiently in Jordan and its neighbors to predict the directions to collect the maximum power.