This study presents a numerical approach to calculate the optimum photovoltaic (PV) tilt angle by considering the three different PV technologies (monocrystalline, polycrystalline, and thin film). This analysis focuses on determination of optimum tilt angle considering seasonal and yearly solar radiation on a plane (Wh/m2) and seasonal and yearly energy production (Wh) of PVs. The angle at maximum global radiation and maximum energy output is considered as the optimum tilt angle. It is found that optimum tilt angles obtained by total radiation and total energy output are different from each other considering seasonal and yearly base. Total radiation-based tilt angle results show that the optimum tilt angle is 13 deg in spring, 9 deg in summer, 17 deg in autumn, 12 deg in winter, and 12 deg as yearly. Energy production-based optimum tilt angles vary from 5 deg to 13 deg for monocrystalline, from 11 deg to 15 deg for polycrystalline, and from 12 deg to 25 deg for thin film technology according to seasonal and yearly tilt angle results.
Photovoltaic (PV) systems are considered as a support unit and eco-friendly energy source for the electric vehicles. If the surface of the electric vehicle is covered by PV cells, it is possible to store considerable amount of energy in the battery system. In this study, different maximum power point trackers (MPPT) with different maximum power point (MPP) tracking algorithms have been tested on a PV structure moving according to a predefined motion loop. Compatibility of each algorithm to moving systems, such as electric vehicles, is presented in a real experimental environment. As a result of these experiments, positive factors in each algorithm have been defined and a new MPP tracking algorithm convenient for moving vehicle has been proposed. The proposed MPPT algorithm shows a better performance than other MPPT algorithms under fast varying radiations. However, proposed algorithm brings slightly higher costs compared to usage of other MPPT algorithms since it requires the measurement of solar irradiance. The developed algorithm is described in detail and comparative analysis and performance evaluation with other algorithms are presented.
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