Marija Demicoli

This study aims to quantify the size and intensity of umbra and penumbra shadows on photovoltaic (PV) modules and assess the resulting potential power loss using image analysis techniques. An innovative algorithm, developed from open-source code, was employed to analyze shadow characteristics, alongside outdoor experiments to measure the raw power loss caused by thin objects shading the PV module. Spearman correlation analysis revealed a weak negative correlation between power loss and object distance, which strengthens with increased object thickness. For larger objects between the range of 10 and 16 mm, the raw power loss is predominantly influenced by umbra intensity, while smaller thin objects in the range between 2.8 and 8 mm are affected more by the intensity of the penumbra shadow. Moreover, beyond a distance of 225 cm, for object thicknesses up to 16mm, umbra shadows disappear, leaving only penumbra, which continues to cause power loss, though at a lower intensity. The study's key findings indicate that thicker objects generate stronger umbra shadows, correlating more significantly with power loss, while thinner objects create diffuse penumbra shadows with a reduced impact. Penumbra size and intensity play a critical role, as larger penumbras correspond to a slower reduction in power loss over distance. Shadow intensity, particularly for thicker objects, proves to be a more decisive factor in the raw power loss output than shadow size, as the increase in shadow size compensates for the loss in intensity. The image analysis techniques developed in this work provide an effective method for objectively quantifying the size and intensity of umbra and penumbra shadows, highlighting the importance of shadow dynamics.

Improving the efficiency of silicon-based solar cells is imperative to maximise harnessing of solar power. The current improvements in efficiency were attained by better manufacturing techniques and purer materials. There is however indirect evidence that the so-called agglomerated grown-in defects in silicon have a direct impact on cell efficiency and if this is the case, the efficiency could be improved by crystal engineering. This study focuses on understanding the defect generation and growth mechanisms in commercial silicon crystals and their impact on cell efficiency. Silicon wafers from different parts of the crystal having a range of oxygen and dopant concentrations and growth profiles, were investigated. These crystals were characterized using various tools and techniques such as Infrared Light Scattering Tomography (LST) to measure the defect density, and Fourier Transform Infrared Spectroscopy (FTIR) to measure the oxygen concentration. Solar cells were then fabricated out of these wafers to measure the performance of the devices. An understanding of why and how such defects impact the yield of different silicon wafers will lead to a thorough understanding of the relationship between the defect types, size and densities and cell efficiency. Moreover, this study will also shed light on the development of crystal recipes or after-crystal procedures to eliminate or minimize these effects on solar cell performance.