https://www.um.edu.mt/library/oar/handle/123456789/1182 2026-04-11T11:30:25Z https://www.um.edu.mt/library/oar/handle/123456789/145062 Title: Experimental analysis of a constant blade to jet speed ratio control for a micro-Pelton wheel turbine for use with an offshore hydro-pneumatic energy storage system Authors: Aquilina, Luke; Duane, Iain; Faust, Wilian; Sant, Tonio; Farrugia, Robert N. Abstract: Hydro-Pneumatic Energy Storage is a type of mechanical energy storage system being investigated for providing long duration energy storage which is becoming essential for integrating renewables on a wide scale. Pelton turbines are often being considered for converting the stored energy into electricity. This is due to the low specific speed requirements, resulting from the high pressure and low flowrates that characterise hydro-pneumatic systems. As opposed to conventional applications in hydro power, where variations in the operating head are small, hydro-pneumatic energy storage presents a more complex environment due to the relatively large variations in the head across the discharging cycle. This study implements a control scheme on a physical setup to maintain a constant blade-to-jet speed ratio for a grid-connected Pelton turbine. The proposed scheme increased the turbine’s overall efficiency from 62 % to 65 %, representing a 4.9 % relative improvement in recovered energy compared with the constant-speed control scheme. 2026-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/145061 Title: Using measure-correlate-predict methodologies for offshore wind resources quantification in a Mediterranean island scenario Authors: Mifsud, Michael D.; Farrugia, Robert N.; Sant, Tonio; La Fata, Davide; Ellul, J. P.; Mule’ Stagno, Luciano; Lauri, A. Abstract: The accurate quantification of long-term wind resources is crucial for the design and optimization of offshore wind farms. This study explored the impact of highresolution Light Detection and Ranging (LiDAR) wind data on wind resources quantification in the central Mediterranean region, focusing on the generation of predicted long-term datasets and on offshore wind energy production. By correlating long-term wind datasets against measured short-term LiDAR data during two separate yet concurrent timeframes, researchers can improve wind speed predictions leading to better informed wind farm planning decisions. Four different Measure-Correlate-Predict (MCP) methodologies available in the windPRO® V4.0 software suite were employed to assess MCP method performance in predicting wind speeds at four specific locations outside Malta’s territorial waters and at one onshore location, where the LiDAR unit itself was situated. The results demonstrated a strong correlation between the long-term data and measured wind speeds during the concurrent time frames. The findings support the use of the MCP methodology and commercially-available long-term offshore wind data for wind farm planning and optimization decisions, particularly in the central Mediterranean region. 2026-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/144897 Title: Correlating field experimentation and image analysis for the assessment of induced losses from thin object shading on photovoltaic sources Authors: Axisa, Matthew; Mule’ Stagno, Luciano; Demicoli, Marija Abstract: This research investigates the correlation between the size and intensity of both umbra and penumbra shadow formation and the resulting power loss, based on field experimention using various thin objects to cast shadows on a photovoltaic (PV) module. The results from the Spearman correlation matrix clearly demonstrate that the significance of both the umbra and penumbra size increases as the thickness of the shading object increases. Additionally, it has been noted that penumbra intensity plays a crucial role in power loss for thin objects ranging between 2.8 and 12mm in thickness. This study identifies the range of distances at which thin objects, ranging from 2.8 mm to 12 mm in thickness, produce zero power loss, indicating no observable effect on the performance of the PV module. By understanding these key aspects, other researchers and PV system owners can better assess the impact of shadow factors on their respective systems. Consequently, the findings from this study are also valuable for determining the impact of certain thin objects typically found on rooftops, helping to optimize the design of PV systems without compromising the functionality of the building. 2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/144888 Title: Quantifying the effect of shadow formation on photovoltaic sources under thin object shading : an image analysis approach Authors: Axisa, Matthew; Mule’ Stagno, Luciano; Demicoli, Marija Abstract: 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. 2025-01-01T00:00:00Z