Abstract:
In this thesis, the advantages of two different maximum power point tracking (MPPT) algorithms has been investigated for a sound solar photovoltaic power conditioning system. By simulation, the performance and efficiency of these algorithms were analyzed by implement in a mppt of a solar photovoltaic power conditioning system as a calculative brain. By using MATLAB‟s SimPowerSystems block set, we created the model comprised of a solar panel powering a buck-boost converter controlled by the MPPT algorithms driving a resistive load. The main objective was to track the maximum power point (MPP) of the solar array by modulating the buck converter‟s duty cycle, thereby, optimizing the power output of the panel. The two algorithms observed performance was on par with other real world tests of these algorithms as seen in other published work. The Perturb and Observe (P&O) algorithm performed with a higher overall efficiency and was able to track the MPP quickly, while the Incremental Conductance (InC) algorithm had similar performance but requires more intensive calculations. The analysis of these algorithms led to a greater understanding of where the inefficiencies of this type of system are located, allowing improvement in future work on this subject.
