Analysis of maximum power tracking methods in photovoltaic panels

Abstract

In the last century, the demand for energy has soared with the rapid development of technology and the human population. The fossil fuels such as coal, natural gas, oil, etc. used today to obtain energy have a limited lifespan. Therefore, the interest in renewable energy sources is increasing. Solar energy, which is one of these renewable energy sources, comes to the fore more than other renewable energy sources because the energy emitted instantly by the sun is so much greater than the energy consumed by the world in a year. Therefore, much research has been done to produce a greater amount of energy from the sun. This study examines the Maximum Power Point Tracking (MPPT) methods that are widely used today. The methods under review include; Constant Voltage, Short Circuit Current, Perturb and Observe, Fuzzy Logic, Incremental Conductance and Artificial Neural Networks. Of these methods, Perturb and Observe, Fuzzy Logic and Artificial Neural Networks have been analyzed using the PVSOL software, which is for making designs and simulations for photovoltaic systems. The analysis includes a comparison of the depreciation periods for the Standard Systems and the facilities where these control algorithms are used.