Due to increased energy demand and harmful effects of fossil fuels there is a tendency towards developing alternative energy sources. One of the methods is Photovoltaic (PV) generators which convert Sun radiation to electricity directly from the Sun as a renewable energy source. The power produced by the PV generator depends on atmospheric conditions and there is a unique maximum power at specific atmospheric conditions due to current versus voltage characteristics of PV generators which are nonlinear. Therefore, the Maximum Power Point Tracking (MPPT) unit is a key parameter of the system in that it provides the tracking of maximum power and operation.
In this thesis, a Fuzzy Logic Controller (FLC)-based MPPT system is suggested, modeled, simulated, and compared with the traditional Perturb and Observation (P&O) method. Using the proposed system provides faster and softer maximum power point tracking. Furthermore, the system allows more stable power at a steady state case. The PV array was employed with the proposed system in both grid-connected and standalone cases. Additionally, it is proposed that power flow management founded on FLC-based MPPT effectively employs the PV system including the backup battery unit in standalone applications. The system operated effectively via the switching of the backup battery power direction as with the proposed MPPT system. All of the studies were digitally executed on the MATLAB/Simulink Simpower simulation platform. The results highlighted the advantages of the proposed system.
Key Words: Solar energy, Photovoltaic systems, Maximum power point tracking, Fuzzy logic controller, Power flow management.