Maximum power point tracking algorithm based on fuzzy logic for improving the performance of the solar energy system

Solar energy is an existing clean and emission-free renewable energy source that has been increasingly adopted in recent years. It is estimated that the solar energy received in less than an hour will be sufficient to meet the one-year budget of the world energy budget. In a photovoltaic (PV) solar system, the power generating devices are PV modules, often referred to as PV panels. The cost of electricity from PV modules is more expensive than electricity from other non-renewable sources. For this reason, the PV system should be operated at maximum efficiency by following the maximum power point in all weather conditions. Maximum power point tracking (MPPT) techniques are considered a crucial part in photovoltaic system design to maximize the output power of a photovoltaic array. MPPT control techniques have been applied to operate the PV module at the maximum operating point where the maximum generated power can be transferred to the load connected through the output terminal of the booster converter. In this study, different MPPT techniques are proposed for stand-alone PV systems in MATLAB/Simulink environment under different conditions. MPPT techniques include the Fuzzy Logic Controller (FLC) compared to Perturb and Observe (P&O). The results of the simulation studies carried out within the scope of the thesis; It has been verified that the output power efficiency of the Fuzzy Logic Controller (FLC) is better than the P&O algorithm, and the FLC-based MPPT controller can monitor the maximum power point (MPP) faster than other recommended controllers in various weather conditions, such as different irradiance and temperature level. Also, fuzzy logic based MPPT algorithms offered significantly lower ripple magnitude in both power and current compared to traditional P&O algorithm.