Optimizing agrivoltaic system configurations for maximum PV energy yield under crop light availability constraints in diffuse-irradiance temperate climates

/ Optimizing agrivoltaic system configurations for maximum PV energy yield under crop light availability constraints in diffuse-irradiance temperate climates

Optimizing agrivoltaic system configurations for maximum PV energy yield under crop light availability constraints in diffuse-irradiance temperate climates

Master internship - Genk | About a week ago

Optimizing agrivoltaic system configurations for maximum PV energy yield under crop lightavailability constraints in diffuse-irradiance temperate climates

Agrivoltaic (AV) systems combine photovoltaic energy generation with agricultural production on the same land, offering a solution to land-use competition between food and energy systems. AV already operates across temperate Europe, including Dutch raspberry farms, where AV structures buffer microclimate comparably to plastic tunnels while generating renewable energy [1]. Broader adoption could support renewable energy targets. However, in temperate climates with high diffuse irradiance fractions, crops receive less total radiation than in Mediterranean or arid regions, making them more sensitive to additional AV shading. Existing studies use generic crop categories without crop-specific PAR (photosynthetically active radiation) thresholds, or evaluate fixed installations without optimizing configuration parameters [2], [3], [4], leaving a gap in understanding how tilt angle, row spacing, and ground coverage ratio influence the trade-off between PV energy yield and crop-level PAR availability. This research asks: how do open-field AV configuration parameters influence this trade-off in diffuse-irradiance temperate climates?

Objectives

• Conduct a systematic literature review on AV simulation methods, crop-specific PAR thresholds, and openfield AV system performance under temperate climates
• Collect and process Belgian meteorological data (irradiance, cloud cover, diffuse fraction) from ERA5 or the Royal Meteorological Institute of Belgium
• Develop a parametric Python simulation model, using existing libraries (pvlib, bifacial_radiance), to calculate PV energy yield and ground-level PAR distribution across varying open-field configurations (tilt angle, orientation, row spacing, mounting height, ground coverage ratio)
• Determine, for each configuration, whether crop-specific PAR thresholds are met for selected Belgian arable crops (e.g. wheat, sugar beet) based on literature values
• Validate the simulation model against measured irradiance and energy yield data from Belgian AV pilot installations [3], and cross-check against published simulation benchmarks
• Evaluate viable configurations using shading ratio, light homogeneity index, specific energy yield (kWh/kWp), and energy yield per unit area (kWh/m²), and formulate design guidelines transferable beyond the Belgian case

Proposed scientific methodology This research combines a structured literature review with parametric simulation and scenario analysis. A Python model will be developed using pvlib and bifacial_radiance, with ERA5 meteorological data as climate input. The model systematically varies tilt angle, orientation, row spacing, mounting height, and ground coverage ratio, calculating PV energy yield and ground-level PAR distribution. A viable configuration is defined as one where PAR remains above the crop-specific light compensation point from agronomic literature. Outputs will be validated against Belgian AV pilot data from [3] and simulation benchmarks from Niazi & Victoria [2]. Performance will be optimized on the PAR ratio (ground-level PAR relative to open-field PAR), with specific energy yield (kWh/kWp) as secondary metric. Belgium is a representative case study due to its high diffuse irradiance fraction (50–60% of global horizontal irradiance, GHI) and temperate oceanic climate, characteristics shared across North-Western Europe.

Type of internship: Master internship

Required educational background: Energy

Supervising scientist(s): For further information or for application, please contact Shu-Ngwa Asaa ( Shu-Ngwa.Asaa@imec.be ) and Arnaud Morlier ( Arnaud.Morlier@imec.be )

The reference code for this position is 2026-INT-235. Mention this reference code in your application.

Only for self-supporting students.

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