https://www.um.edu.mt/library/oar/handle/123456789/6578 2026-06-08T09:53:46Z 2026-06-08T09:53:46Z https://www.um.edu.mt/library/oar/handle/123456789/146869 2026-05-28T09:06:45Z 2025-01-01T00:00:00Z

Title: Comparing photoluminescence imaging and microwave detected photoconductivity for measuring recombination lifetimes of silicon wafers Abstract: This study investigates the correlation between recombination lifetime and photoluminescence (PL) in silicon solar cells, aiming to evaluate the reliability of Photoluminescence Imaging (PLI) as compared to the well-established Microwave Detected Photoconductivity (MDP) technique. Recombination lifetime is a critical parameter influencing solar cell efficiency, as it determines how long charge carriers persist before recombining. Using both MDP and PLI tools, the recombination lifetimes and corresponding PL grey values of monocrystalline silicon wafers were measured under various thermal and contamination conditions. Heat treatments at 800°C and 950°C, along with deliberate contamination using a copper coin and latex gloves, were employed to produce a wide range of recombination activity across the samples. Data were analysed using ImageJ to correlate PL grey values with MDP-measured lifetimes. A linear relationship of the form Y = 0.0090X, where Y is the recombination lifetime and X is the grey value, was established through regression analysis. Results revealed a consistent relationship between the two measurement techniques, validating the potential of PLI as a rapid and non- destructive proxy for lifetime assessment. The findings support the development of cost-effective and efficient quality control methods in photovoltaic manufacturing by leveraging the complementary strengths of both PLI and MDP. Description: M.Sc.(Melit.)

2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/146070 2026-04-30T09:55:21Z 2025-01-01T00:00:00Z

Title: Shared micro-mobility services : a sustainability assessment of their use in Malta Abstract: Shared micro-mobility services in Malta, such as bicycles, e-bikes and e-scooters, were analysed in this dissertation. Literature shows that shared micro-modes of transport pose several benefits, such as reduced traffic congestion and the promotion of an active alternative mode of commuting, posing cost-effective, health and social benefits. They are ideal for last mile trips and work extremely well when properly integrated with the transport system, particularly the road infrastructure and public transport systems. Shared micro-mobility services reduce the energy demand and have the potential of reducing carbon and greenhouse gas (GHG) emissions on local roads. Although in 2016 shared micro-mobility services were introduced in Malta, these abruptly halted their services. Thus, the aim of this thesis was formulated as follows: To perform a sustainability assessment on shared micro-mobility services in Malta, to understand their sustainability advantage, the reasons why they stopped operating, and to make recommendations for their inclusion in sustainable transport locally. The methodology to gather data was semi-structured interviews with 18 key stakeholders of transport in Malta. A simplified sustainability assessment and policy review were also conducted. Results show that the majority of participants perceived them as sustainable and that there needs to be a competitive advantage over other modes of transport (particularly the private car), the provision of safe infrastructure and better enforcement. Participants also claimed that the main reasons why they left was due to abuse, chaos, no discipline (especially amongst e-scooter users), vandalism and lack of safety towards pedestrians and other road users; with 40% of the respondents agreeing with these services halting operations. The Maltese government is looking towards the future, providing incentives for the use of personalised e-bikes and e-scooters. However, sharing services are still not being pushed to reintroduce them. Although private micro-vehicles may reduce the abuse, irregularities and dangers to self or pedestrians, they do not eliminate them. Shared services still have the potential to provide a cheap, flexible and convenient alternative to commuting, and its potential (considering Malta’s size) should not be ignored. Key concluding recommendations include the need for pilot projects, an enhanced regulatory framework and enforcement, more awareness and acceptance, improved public transport (bus/ferry) and integration, and the provision of safe infrastructure. Description: M.Sc.(Melit.) Sust.Energy

2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/144597 2026-03-04T14:08:51Z 2025-01-01T00:00:00Z

Title: A study on the effect of thin object shading on the performance of photovoltaic modules Abstract: This study investigates a specific and underexplored aspect of partial shading of photovoltaic (PV) systems that is caused by thin horizontal objects. Following a review of both fundamental principles and current state-of-the-art, the primary aims were to examine differences in shadow formation and associated power loss between laboratory and outdoor environments, quantify shadow formation characteristics, and to assess the scientific validity of commonly used simplifications in representing penumbra shadows. This study presents a comparative analysis of thin object shadows under laboratory environment conditions using a solar simulator, and under outdoor environmental conditions. Using a 156.0 × 156.0 mm solar cell, 56 thin object shading cases were compared using thin objects of thicknesses of ⌀2.0 mm - ⌀20.0 mm at distances between 10 cm – 40 cm in 5 cm increments. The solar cell placed in outdoor conditions produced higher power losses in the range of 0.34 W - 0.67 W, equivalent to 8.18% to 16.13% power loss respectively, when converted to standard test conditions (STC). This observation was validated by producing a quantitative factor which incorporated both the size and intensity of the overall shadow at equal weight where clearly the outdoor environment produced stronger shadow formation. Moreover, the image capture of all 56 cases found evidence of the laboratory environment producing fringed shadow patterns caused by Fresnel diffraction on the thin objects, most evidently in the shadows of the smallest thin object (⌀2 mm). This thesis also implemented a novel methodology to quantify the shadow formation and the power loss of 104 thin object shading cases, using custom made image analysis tool named ThinShadePV. This tool utilises image analysis and Random Forest machine learning to determine the size and intensity of umbra and penumbra shadow regions from captured shadow images and predict the associated power losses. Validation through 15 real-world thin shadow cases demonstrated strong agreement between predicted and actual power loss values, with a mean deviation of just 0.48% and an accuracy range of –3.68% to +2.71%. Moreover, Spearman correlation and sensitivity analyses revealed that penumbra intensity is the most influential factor for smaller objects (⌀2.8–⌀8.0 mm thick), while the size of the umbra shadow dominates in larger objects (⌀10–⌀16.0 mm) thick. The study also assessed the validity of approximating varying-intensity penumbra shadows with constant-intensity penumbra representations using neutral density (ND) filters. While constant-intensity shadows closely replicated the relationship profile, they consistently overestimated power loss, despite matching the size and average varying intensity shadows. A large effect size (Cohen’s d = –0.893) confirmed a significant discrepancy, indicating that varying-intensity penumbra shadows should not be simplified to constant-intensity models in analytical or simulation contexts. One of the key contributions of this study lies in its significant advancement of current knowledge by empirically quantifying the effects of horizontal thin object shading on PV performance and establishing key relationships between shading parameters and power loss. The development of ThinShadePV, a purpose-built image analysis tool, enables quantitative measurement of shadow characteristics and power loss prediction. Moreover, ThinShadePV holds strong potential for integration into commercial PV simulation software, enhancing the accuracy of performance forecasts under real-world shading conditions. Description: Ph.D.(Melit.)

2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/141615 2025-12-12T06:48:44Z 2023-01-01T00:00:00Z

Title: On the use of measure-correlate-predict methodologies and energy demand forecasting to assess energy storage capabilities for offshore wind farms Abstract: Energy storage is crucial for the continued penetration of renewable energy. One of the most important reasons for this is that, for a given point of time, the availability of renewable energy resources rarely matches the demand for electrical energy. The integration of offshore windfarms with energy storage facilities, requires a capital-intensive investment which can only be justified by an adequate return on investment (ROI). Currently, Measure-Correlate-Predict (MCP) analysis is used to assess the viability of offshore windfarms while energy demand forecasting is normally used to manage and plan the electricity grid infrastructure. This research combined wind energy prediction methodologies with Energy Demand Forecasting (EDF) methodologies to size the energy storage capacity for an offshore windfarm and evaluated the economic feasibility. This research analysed various regression techniques for MCP analysis. Data from a Light Detection and Ranging (LiDAR) system were utilised. The study was extended to analyse the behaviour of a hypothetical floating windfarm, situated off the Northern Coast of the Island of Malta. The effect of using the different regression techniques for MCP analysis on the power output from the windfarm could therefore be evaluated. The second part of the research used a combination of ARIMA and regression techniques to forecast the energy demand over several years. The output from the windfarm was applied to a model which integrated the said windfarm to an Energy Storage System (ESS) and the electricity grid. Measurement matrices were used to compare the behaviour of the combined windfarm, ESS and electricity grid, based on the actual and predicted data from the various regression techniques used for the MCP analysis and EDF. This created a matrix of results which was used to determine the optimal combination of regression techniques used for MCP analysis and EDF, following which, the optimal capacity of the ESS was established. The long-term behaviour of the windfarm and the of the energy storage system were also predicted. The Levelised Cost of Energy (LCOE) for the windfarm and the Levelised Cost of Storage (LCOS) for the Energy Storage System were also calculated, using different windfarm scenarios, and analysing the error due to the use of the MCP and EDF methodologies. This research therefore established a methodology for combining MCP and EDF to determine the optimal capacity of an ESS which was coupled to an offshore windfarm and the electricity grid. The error in establishing this capacity was determined. The end result was the determination of the LCOE of the windfarm and the LCOS of the ESS based on the combination of MCP analysis and EDF, together with the error introduced due to the use of the two methodologies. Description: Ph.D.(Melit.)

2023-01-01T00:00:00Z