Yield modeling of agrivoltaic concepts

To mitigate the ongoing climate change, carbon-neutral sources of energy are required. Large scale photovoltaic (PV) systems are considered one of the most promising technologies in this regard, as they have proven to be a green, cheap and reliable energy source. With the exponential growth of installed PV capacities worldwide, direct land-use changes have been triggered as ground-mounted PV systems have been installed on arable land formerly used for food production. However, renewable energy does not threaten agricultural production; indeed, they can coexist in the concept of agrivoltaics (APV). Describing the combination of agriculture and PV energy production on the same plot of land, APV is a promising solution when it comes to meeting the growing demand for both food and energy while also addressing land use conflicts. This thesis presents the development and validation of a simulation tool for APV greenhouses (GHs). The model enables the simulation of irradiance levels under APV conditions within GHs and gives an estimation of crop yield. The ray-tracing-based irradiance model focuses on mapping light transmission through GH cover materials and PV modules. The crop model includes two different approaches. One approach is based on daily light integral (DLI) requirements of different crops. The second approach focuses particularly on tomatoes and uses a functional-structural plant model (FSPM). The irradiance model was validated using both data from literature and experimentally measured data from an APV GH experiment performed from September 2023 to March 2024. The experiment was conducted in a "raspa y amagado" GH in Almería, Spain, and two roof cover ratios of 30% and 50% shading were compared against an unshaded control zone. The nRMSE of the global horizontal irradiance was determined to be 0.09 for the control zone, 0.18 for 30% shading and 0.27 for 50% shading using the irradiance data from the experiment. For the literature-based validation, a "Venlo"-type APV GH experiment from 2014–2015 was reproduced, resulting in a deviation of 2.88 percentage points in the simulated reduction in radiation over the entire crop cycle. The crop model was validated exclusively with data from the 2023–2024 APV GH experiment. The nRMSE of yield of the DLI analysis for the simulated crop cycle was 0.10 for the control zone, 0.07 for 30% shading and 0.06 for 50% shading. The validation of the FSPM approach yielded an nRMSE of dry weight of 0.04 for the unshaded control zone and 0.07 for the 30% shading zone, while the data from the 50% shading zone was used to calibrate the model. The economic assessment of the experimental APV GH showed a potential profit increase of +15% under the case of 30% of the GH roof covered with PV. For the 50% cover scenario, the economic profitability increased to 22% for one tomato crop cycle. The developed simulation tool provides a solid foundation for modeling the irradiance distribution within APV GHs and assessing its effects on expected crop yield. It can serve in the future as a basis for deriving optimal APV GH designs tailored to specific locations, climate conditions and crop types.