Ünlütürk, MuhammedKulaksız, Ahmet AfşinÜnlütürk, Ali2024-09-042024-09-042019978-1-5386-8086-5https://hdl.handle.net/20.500.13091/6153Numerous environmental factors significantly affect the energy yield of solar photovoltaic (PV) power plants. Among these, solar irradiance, photovoltaic module temperature, dust and shading are prominent. The level of soiling is directly related to the installation site of the PV plant. In this study, to investigate the impact of dust shading factor on energy efficiency, artificial light source in laboratory environment is used and power outputs are compared for three different densities of dust accumulation on the module surface. For each level of dust accumulation, images are obtained from PV modules. From the PV module images obtained by a camera for different levels of dust accumulation, new features are obtained based on Gray Level Co-occurrence Matrix. The obtained data with new features are classified on the basis of Artificial Neural Networks to determine dust level and its effect on PV module performance.eninfo:eu-repo/semantics/closedAccessSoilingDust depositionPhotovoltaic moduleSolar energyConference Object