RBF Neural Network Model to Increase the Performance of Solar Panels

Abstract

One of the significant sources of environmental conservation is the utilization of renewable energy. Renewable energy is the energy derived from natural sources that are replenished automatically from unlimited sources. In this paper, we study the solar energy and how to increase the performance by solving the problem of dust and dirt accumulated on solar cells. Dust and dirt are the most important reasons that reduce the performance of solar cells in natural conditions. We use artificial intelligence neural networks to make the decision that solar cells need to be cleaned. Moreover, we propose two scenarios and we compare them. In the first scenario, the variables, temperature, weather and humidity are considered and in the second scenario, the variables, temperature, weather, light Intensity and humidity are considered. Concerning the weather conditions, a system prediction based on previous years is done. Results show that this system increases the solar cells’ performance by cleaning the dust and dirt in correct time.