AbstractsComputer Science

ABSTRACT Maximum Power Point Tracking (MPPT) plays an important role in Photovoltaic Generation (PVG) systems because it maximizes the power output from a PVG system. Thus, an MPPT can minimize the overall system cost. MPPT operates a PVG system under different solar irradiances and temperatures. Many such algorithms have been proposed. This thesis provides a comparison between Perturb and Observe (P&O) method, and Particle Swarm Optimization (PSO) method with the weather data from Taiwan Weather Bureau. Matrix Laboratory (MATLAB) programming by using real data is implemented for a PVG system with a rated output of 200 W energy to obtain the curve performance and the unharvest energy for different the MPPT algorithms. Advisors/Committee Members: Rong-Ceng Leou (chair), Chun-Lien Su (chair), Jen-Hao Teng (committee member), Cheng-Ting Hsu (chair).