Fuzzy Logic-based Power Optimizer for Solar Photovoltaic Power Systems

Abstract

Solar photovoltaics has become the most popular renewable energy source due to its simplicity in installation and maintenance. However, the dependence on the availability of solar energy at the instant makes its operation non-linear. Various optimizing solutions are proposed to rule out this disadvantage. This paper dwells on a machine language approach to solve this problem. A maximal tracker for power points relies on fuzzy logic control. An embedded power optimizer is designed and tested under different environmental conditions through simulation. The results presented allow researchers to test various artificial intelligence techniques for renewable energy extraction processes.