Ocean surface albedo (OSA) is the fraction of incoming solar radiation reflected back by the ocean surface, driven mainly by wave geometry, whitecaps, and subsurface components like chlorophyll and mineral particles. The accurate modelling of this parameter is from importance for offshore floating photovoltaics (OFPV), where the bifacial panels can be used to boost the energy yield, impacting the levelized cost of electricity (LCOE) and energy transition strategies.
Current albedo datasets lack accuracy when considering OSA as a constant value, which is an oversimplification that ignores the sea dynamics. Moreover, the spatial resolution of these sources is commonly 1/24° (about 4km), which is a coarse resolution considering that the characteristic length scale of an OFPV plant is in the order of 1km. Empirical models focused specifically on OSA modeling exhibit an improvement compared to the existing datasets; however, they fall short by not including all the parameters that effectively influence OSA, and their empirical nature, which makes their accuracy location-specific. This thesis addresses these gaps, developing and validating a model based on GenPro4 to estimate OSA in realistic ocean scenarios.
The proposed model was tested in two main waterbodies classes: clear and turbid waters, to analyze and determine its accuracy under these two opposite sea states. Root mean square errors (RMSE) values of 0.72% for clear and 3.8% for turbid waters confirmed its robustness and reliability. Furthermore, a sensitivity analysis was executed to identify the key parameters that affect the bifacial gain when considering the dynamic nature of OSA, finding that sea roughness (waves geometry) defined by the significant height wave (Hs) and its peak period (Tp), had a significant effect, producing bifacial gain changes close to 3.5% between calm cases and rough wave scenarios.
Finally, regional simulations on four locations across the globe revealed that despite seasonal variations of bifacial gain, an annual average value ranging from 5 to 8% is obtained regardless of the specific location of the OFPV plant. These findings confirm that bifacial gain varies with different sea states but remains within a predictable and practical range for OFPV design and performance assessment.
Economically, this 5–8% yield uplift offsets the additional CAPEX from bifacial panels, potentially achieving breakeven or lower LCOE values compared to monofacial cases. Dynamic OSA thus drives bifacial viability, confirming competitive OFPV performance across oceans. ... Read more

Floating Photovoltaic (PV) system is an emerging and rapidly developing solar PV application that utilizes water surfaces, such as reservoirs and lakes, as the installation grounds for the PV arrays and its balance of systems. In addition to becoming a solution to land scarcity issues of solar PV installation, floating PV systems also benefit from an improved thermal performance due to its proximity to water that results in a cooling effect for the PV modules. However, the extent of this cooling effect is not yet well-understood and established. Conventional thermal modelling tools and approaches, which are mostly validated for land-based PV systems, might not be directly applicable to floating PV systems without proper adaptation. This research aims to improve the accuracy of temperature and energy yield predictions for floating PV systems by evaluating and updating physics-based thermal models based on both analytical and computational methods. This study is driven by several research questions, which includes the analysis on how do existing thermal models perform in predicting floating PV module temperatures, how can Computational Fluid Dynamics (CFD) simulations be used to improve thermal models accuracy for floating PV applications, and how does the improvement in thermal model accuracy impact energy yield estimation in PV system energy yield simulation tools.

Chapter 2 conducts an evaluation of two analytical thermal modelling approaches for predicting floating PV module temperature, which are the Fuentes Model and the Resistive Thermal Model. Results show that while both models reasonably capture the PV module temperature trends, they tend to under-predict water-induced cooling effect that is present in floating PV environments, which results in a overestimation of PV module temperatures in general. Even though the Resistive Thermal Model results in a slightly higher accuracy compared to the Fuentes Model, a notable Root Mean Square Error (RMSE) is still observed with respect to measured values. This discrepancy highlights the need to improve the thermal dynamics representation, especially in capturing the effect of water proximity and the modified convective heat transfer interactions unique to floating PV systems. Chapter 3 implements CFD as a refinement tool for the analytical thermal modelling, with the goal of combining CFD's ability to capture detailed solid-fluid interactions and the computational cost effectiveness of the Resistive Thermal Model. The CFD-Updated Resistive Thermal Model is compared against measured data and shows a substantial RMSE reduction, with an RMSE of 0.72oC, significantly lower than the RMSE of the initial Resistive Thermal Model (1.70oC) and the Fuentes Model (2.30oC). Chapter 4 analyses how the improved thermal models affect energy yield prediction by using two simulation tools PVsyst and the PVMD Toolbox. The energy yield results show that the CFD-updated Resistive Thermal Model achieves the closest match to the measured specific energy yield, with an error of just 0.10%, compared to 1.75% and 1.27% error values for the Fuentes FD Model and the initial Resistive Thermal Model, respectively. These results clearly show that the increase in thermal model accuracy is directly related to a higher accuracy in energy yield simulation, where the energy yield simulation based on the improved thermal model results in a very close agreement with measured values. Chapter 5 focuses analysing how does practical installation scenario, specifically differing PV array row spacing, affect the thermal dynamics of floating PV systems. The results demonstrate that while close-proximity PV arrays with small row-spacing may offer higher power density per unit area, it comes at the cost of increased PV module temperatures and potentially reduced energy yield. On the contrary, large-proximity PV arrays with large row-spacing results in a lower overall PV module temperatures that potentially increase energy yield of the floating PV system.

In conclusion, this study demonstrates the important role of thermal modelling in improving floating PV performance prediction for floating PV systems. The integration of CFD-derived parameters into Resistive Thermal Model leads to significantly improved accuracy in temperature and energy yield predictions. However, the findings are based on limited real-world measurement data and a single floating PV archetype. A more extensive validation across more configurations and climates, as well as the development of generalized Nusselt number correlations for diverse floating PV archetypes are recommended for future works.
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As the global community seeks to improve current energy technologies for a sustainable future, offshore PV systems show great potential to overcome the land use limitations of traditional PV systems. There is a complex interaction between different environmental forces at sea with the PV structure. Empirical studies on these environmental interactions can provide critical insights to optimize the design of offshore PV systems. This thesis has identified a gap in wind loading studies on offshore PV designs. The primary objective of this research is to develop a methodological approach for studying the wind-induced tilt variations in floating PV (FPV) systems, with the intent of informing future PV performance assessment frameworks. A numerical modelling approach using the CFD tool ANSYS Fluent is adopted as the base methodology. The first phase of the study employs single-phase wind tunnel models in 2D and 3D to study flow behaviour over the required geometry. The models are validated against literature and used as the basis to construct a multi-phase model to simulate wind flow over a floating body and how it moves in response to the water surface.

The model is used to perform sensitivity studies on wind speed, module orientation, module tilt, and floater height. The simulation results indicate that tilt variations induced by wind flow are minimal, under 5◦, for still water conditions. In addition, it also suggests an increase in wind velocity increases the non-linearity in the rotational response of the body, changes in the direction of rotation depending on the speed of the flow and tilt of the module, and a sharp increase in rotation with an increase in floater height. The highest rotational response of 4.07◦(anticlockwise) was observed for a design tilt of 24◦ and a wind speed of 40 m/s.

Based on the simulation results, a PV yield assessment is done, and it is found that the inclusion of tilt effects changes the yield by less than 0.5%. Given the high computational cost involved, a numerical approach for wind load evaluation is not justified in terms of yield variation. For future work, it is recommended to first conduct experimental studies to verify the effects of wind loading on different FPV system designs. This could be supplemented with numerical approaches in the future using high-performance computational resources.

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