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Energy conversion from conventional ground-mounted photovoltaic systems requires a significant amount of land, which can compete with food production. Agrivoltaic systems, which integrate electricity generation and crop production, can help reduce this land competition. The profitability of agrivoltaic systems is expected to be a crucial factor for decision-makers and stakeholders considering their adoption. This work aims to analyze the economic performance of one-axis, vertical and elevated agrivoltaic systems compared to conventional ground-mounted photovoltaic systems across Europe focusing on countries such as Sweden, Denmark, Germany and Italy. By employing a stochastic approach with Monte Carlo simulations, this research makes a significant contribution to forecasting the profitability and cost-effectiveness of agrivoltaic projects in European countries for the next years. Moreover, it identifies the key parameters that significantly impact the net present value and levelized cost of electricity. The economic findings reveal a notable trend: agrivoltaic projects (i.e., one-axis, vertical, and elevated) are likely to be profitable throughout Europe. However, the agricultural profit generated from these systems is minimal for the investigated crop rotations compared to the benefits derived from energy conversion. Among the systems evaluated, one-axis agrivoltaic setups demonstrate higher profitability and cost-effectiveness compared to vertical and elevated setups. They also have a shorter discounted payback period and a lower levelized cost of electricity than conventional ground-mounted photovoltaic systems. These findings are particularly significant for decision-makers and stakeholders involved in developing agrivoltaic policies. This is especially relevant for Sweden which currently lacks agrivoltaic policies, regulations, and definitions, in contrast to Germany and Italy where policies for promoting agrivoltaics have previously been implemented or are in progress. 

Agrivoltaic systems represent an intelligent solution combining electricity production from solar photovoltaic technology with agricultural production to avoid land use conflicts. Geographic Information System technologies can support the implementation and spread of agrivoltaic systems by identifying the most suitable areas using useful spatially explicit information concerning techno-agro-socio-economic criteria. In this study, we have developed a procedure to identify and classify suitable areas for agrivoltaic systems in Sweden. An Ordinal Priority Approach based multi-criteria decision-making algorithm is established to calculate the weights of the selected evaluation criteria through expert interviews. The land use data refers to the Corine Land Cover 2018 product. The results show that about 8.6% of the Swedish territory, approximately 38,485 km2, is suitable for installing agrivoltaic systems. Among this area, about 0.2% is classified as “excellent”, about 15% as “very good”, about 72% as “good”, about 13% as “moderate”, and about 0.1% as “poor”. Most “excellent”-classified areas are in Kalmar, Skåne, and Gotland. In contrast, most “very good” sites are in Skåne, Kalmar, and Östergötland. By deploying vertically mounted agrivoltaic systems with bifacial photovoltaic modules, the total potential installed capacity for “excellent” areas is about 2.5 GWp, while for areas classified “excellent” and “very good” is about 221 GWp. The total “excellent” areas can potentially supply about 2.4 TWh of electricity against the electricity consumption in 2021 of about 143 TWh. On the other hand, the land classified as “excellent” and “very good” could potentially provide about 207 TWh. The County of Västra Götaland shows the greatest potentials in terms of total potential electricity supply from agrivoltaic systems with about 227 TWh, followed by Skåne with a total potential of 206 TWh. 

Agrivoltaic systems emerge as a promising solution to the ongoing conflict between allocating agricultural land for food production and establishing solar parks. This field experiment, conducted during the spring and summer seasons of 2023, aims to showcase barley production in a vertical agrivoltaic system compared to open-field reference conditions at Kärrbo Prästgård, near Västerås, Sweden. The dataset presented in this article encompasses both barley kernel and straw yields, kernel crude protein levels, starch content in kernels and thousand kernel weight. All collected data underwent analysis of variance (ANOVA) with Tukey pairwise comparison when possible, using dedicated software RStudio 4.3.2. This dataset article illustrates the effects of the vertical agrivoltaic design system on barley productivity. Interested researchers can benefit from this data to better comprehend barley yield under this specific agrivoltaic design and conduct further analyses and comparisons with yields from different locations or design configurations. The experimental data holds the potential to foster collaborations and advance research in agrivoltaic systems, providing a valuable resource for anyone interested in the subject. It was observed that the mean barley yield in all the different areas of the vertical agrivoltaic system were higher than the one in the control area. Additionally, weather and solar irradiance data collected during the growing season are provided in the repository for further usage.

Agrivoltaic systems, which allow the coexistence of crop and electricity production on the same land, are an integrated water–energy–food nexus solution that allows the simultaneous attainment of conflicting Sustainable Development Goals. This study aims to analyse experimental results on the responses of ley grass yield and quality to shadings in the first agrivoltaic system in Sweden. It also aims to validate an integrated modelling platform for assessing agrivoltaic systems' performances before installation. An economic analysis is carried out to compare the profitability of agrivoltaic versus conventional ground-mounted photovoltaic systems and, using a Monte Carlo Analysis, to identify the parameters that most affect the profitability. Despite the agrivoltaic systems’ supporting structures and photovoltaic modules producing an average ∼25% reduction in photosynthetically active radiation at ground level, no statistically significant difference was observed between the yield of the samples under the agrivoltaic system compared to the yield of the samples in the reference area. The agrivoltaic system attained land equivalent ratios of 1.27 and 1.39 in 2021 and 2022, respectively. The validation results of the integrated modelling platform show that the sub-model concerning the crop yield response to shading conditions tends to underestimate ∼7% the actual average crop yield under the agrivoltaic system. The results of the economic analysis show that, from a net present value perspective, agrivoltaic systems have a profitability that is ∼30 times higher than a conventional crop rotation in Sweden.

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.

Photosynthetically active radiation is a key parameter for determining crop yield. Separating photosynthetically active radiation into direct and diffuse components is significant to agrivoltaic systems. The varying shading conditions caused by the solar panels produce a higher contribution of diffuse irradiance reaching the crops. This study introduces a new separation model capable of accurately estimating the diffuse component from the global photosynthetically active radiation and conveniently retrievable meteorological parameters. The model modifies one of the highest-performing separation models for broadband irradiance, namely, the Yang2 model. Four new predictors are added: atmospheric optical thickness, vapor pressure deficit, aerosol optical depth, and surface albedo. The proposed model has been calibrated, tested, and validated at three sites in Sweden with latitudes above 58 °N, outperforming four other models in all examined locations, with R2 values greater than 0.90. The applicability of the developed model is demonstrated using data retrieved from Sweden's first agrivoltaic system. A variety of data availability cases representative of current and future agrivoltaic systems is tested. If on-site measurements of diffuse photosynthetically active radiation are not available, the model calibrated based on nearby stations can be a suitable first approximation, obtaining an R2 of 0.89. Utilizing predictor values derived from satellite data is an alternative method, but the spatial resolution must be considered cautiously as the R2 dropped to 0.73.

Agrivoltaic systems offer a solution to the debate over using agricultural land for food production or energy conversion. Conventional silicon solar panels often shade plants excessively, impacting growth. Wavelength-selective photovoltaic (WSPV) technologies address this by allowing the transmission of beneficial wavelengths for photosynthesis while converting less useful ones into electricity. Wavelength selectivity can be achieved through various methods, such as by tuning photoactive layers, applying colored semi-transparent layers, utilizing mirrors and lenses, or designing spectrally selective luminophores. While evidence suggests that these technologies effectively share sunlight, many of them are yet to be fully implemented and evaluated. This review covers current WSPV technologies, discussing their classification, status, and future prospects. It also provides appropriate PV performance metrics for WSPV technologies in agricultural applications and advocates for standardized reporting practices in crop experiments conducted under WSPV systems, accompanied by practical suggestions. Solar cell efficiency limits under spectral sharing for crop production and the optimal band gap under varying levels of photosynthetically active radiation for crop growth are further examined as guidance for future development.

This study investigates the performance of agrivoltaic systems employing bifacial photovoltaic modules. A comparison between yield in Sweden and Italy was carried out. Three agrivoltaic system designs were evaluated: vertical fixed, single-axis tracker, and dual-axis tracker. The results showed that the specific production varied between 1090 to 1440 kWh/kWp/yr in Sweden and 1584 to 2112 kWh/kWp/yr in Italy, where the lowest production was obtained with the vertical fixed agrivoltaic system while the highest production was obtained with the dual-axis tracking agrivoltaic system. The vertical fixed design had a higher electricity production during low solar elevation angles, while the single-axis and dual-axis tracking designs had significantly higher power production during mid-day. The electricity production gain using a dual-axis tracker design was mostly during mid-day, but the increase compared to the single-axis tracker was only 1-2%. The study concludes that low-height, fixed agrivoltaic systems without tracking are well-suited for high-latitude countries like Sweden, while elevated systems with tracker solutions are more suitable for locations like Italy. The findings suggest that the performance of agrivoltaic systems with bifacial photovoltaic modules is highly dependent on geographical location and the specific characteristics of the crops grown beneath them.

The increasing worldwide population is leading to a continuous increase in energy and food demand. These increasing demands have led to fierce land-use conflicts as we need agricultural land for food production while striving towards renewable energy systems such as large-scale solar photovoltaic (PV) systems, which also require in most of the cases agricultural flat land for implementation. It is therefore essential to identify the interrelationships between the food, and energy sectors and develop sustainable solutions to achieve global goals such as food and energy security. A technology that has shown promising potential in supporting food and energy security, as well as supporting water security, is agrivoltaic (AV) systems. This technology combines conventional farm activities with PV systems on the same land. Understanding the microclimatic conditions in an AV system is essential for an accurate assessment of crop yield potential as well as for the energy performance of the PV systems. Nevertheless, the complex mechanisms governing the microclimatic conditions under agrivoltaic systems represent an underdeveloped research area. In this study, a computational fluid dynamics (CFD) model for a vertical AV system is developed and validated. The CFD model showed PV module temperature estimation errors in the order of 0–2 °C and ground temperature errors in the order of 0–1 °C. The shading caused by the vertical PV system resulted in a reduction of solar irradiance by 38%. CFD modelling can be seen as a robust approach to analysing microclimatic parameters and assessing AV system performance.

Agrivoltaic systems are becoming increasingly popular as a crucial technology for attaining multiple sustainable development goals, such as affordable and clean energy, zero hunger, clean water and sanitation, and climate action. However, a comprehensive understanding of the shading effects on crops is essential for choosing an optimal agrivoltaic system, as an incorrect choice can result in significant crop yield reductions. In this study, fixed vertical, one-axis tracking, and two-axis tracking photovoltaic arrays were developed for agrivoltaic applications to analyse the shading conditions on the ground used for crop production. The models demonstrated remarkable accuracy in comparison to commercial software such as PVsyst® and SketchUp®. These models will help to reduce crop yield uncertainty under agrivoltaic systems by providing accurate photosynthetically active radiation distribution at the crop level. The photosynthetically active radiation distribution was further analysed using a light homogeneity index, and the results showed that homogeneity and photosynthetically active radiation reduction varied significantly depending on the agrivoltaic system design, ranging from 86% to 95%, and 11% to 22%, respectively. Studying the effect of shading with distribution analysis is crucial for identifying the most suitable agrivoltaic system layout for specific crops and geographical locations.