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Increasing global electricity consumption and population growth have resulted in conflicts between renewable energy sources, such as bioenergy and ground-mounted photovoltaic systems, owing to the limited availability of suitable land caused by competing land uses. This challenge is further compounded by the intertwined relationship between energy and agri-food systems, where approximately 30% of global energy is consumed. In addition, considering that agricultural irrigation accounts for 70% of water use worldwide, its impact on both land and water resources becomes a critical concern. Agrivoltaics offers a potential solution to this land use conflict. However, a knowledge gap remains regarding the impact of integrating these techniques on microclimatic conditions. Addressing this gap is crucial because these conditions directly affect the growth and development of crops, as well as the efficiency of energy yields in photovoltaic panels. Experimental facilities offer valuable insights tailored to specific locations and system designs. Although they provide an in-depth understanding of a particular location, the extrapolation of this information to different locations or alternative systems may be limited. Therefore, the broader applicability of these insights to diverse settings or alternative systems remains unclear. In this thesis, a modelling procedure was developed to evaluate the photosynthetically active radiation reaching crops in typical agrivoltaic configurations across three diverse geographical locations in Europe. This is essential for understanding how solar panel shading affects the incoming photosynthetically active radiation required for crop photosynthesis. Furthermore, computational fluid dynamics were employed to model and assess the microclimate of an experimental agrivoltaic system. The developed model revealed significant variations in photosynthetically active radiation distribution across different agrivoltaic systems and locations, emphasising the need for tailored designs for optimal energy yield and crop productivity. Computational fluid dynamics analysis demonstrated its effectiveness in evaluating microclimatic parameters such as air and soil temperature, wind speed, and solar irradiance within agrivoltaic systems, providing valuable insights for system optimisation. By bridging a knowledge gap, this thesis contributes to the understanding of the modelling and simulation of agrivoltaic system microclimates, thereby facilitating the sustainable coexistence of renewable electricity conversion and agriculture.

Agrivoltaic (APV) systems, where photovoltaic (PV) modules are co-located with crops, present a promising solution to land-use competition between food and energy conversion. Their successful deployment, however, requires a nuanced understanding of the trade-offs between electricity generation, crop yield, water use, and regulatory constraints. In this dissertation, a comprehensive modelling framework was developed to evaluate the technical, environmental, and economic performance of APV systems across diverse European contexts. The work builds on advances in irradiance transposition modelling, view-factor analysis, and crop yield estimation, which together enable more accurate characterisation of light distribution and photosynthetically active radiation (PAR) under different system designs. A state-of-the-art review of APV modelling approaches further situates these contributions within the wider field and identifies critical gaps in integrated assessment and validation. On this foundation, scenario-based optimisation was applied to explore system performance across varying climates, row pitches, heights, and orientations, under constraints reflecting national APV regulations. 

A novel combination of LER-based (land equivalent ratio, comparing the combined energy and crop productivity to their separate cultivation) metrics and economic indicators was used to characterise outcomes, with results evaluated over multiple weather years. The findings show that design modifications in geometric layout, particularly row pitch and orientation, can significantly shift the balance between LER_crop and LER_PV, affecting both productivity and profitability. Results further reveal that regulatory thresholds strongly influence feasibility: while strict national frameworks rendered most configurations unviable, relaxed rules enabled designs achieving LER values above 1.3 and net present values (NPVs) exceeding €2 million per hectare. If crop models were to incorporate adaptive mechanisms, even stricter regulatory scenarios could become feasible, with LER values above 1.6 in favourable contexts. Overall, this dissertation contributes transparent and generalisable modelling tools that link detailed irradiance and crop representation with system-level optimisation. The findings underscore the importance of integrating economic, agronomic, and policy perspectives, while pointing to future work on crop model realism, spectral and microclimate effects, and expanded crop databases to further enhance the robustness of APV deployment strategies.