/A deeper understanding of partial shading effects in advanced PV modules

A deeper understanding of partial shading effects in advanced PV modules

PhD - Genk | Just now

Improve photovoltaics module performance under partial shading conditions for integration in facades, vehicles, floors, .... everywhere!

With an increasing demand for (electrical) energy at low cost, with a low environmental footprint and minimal extra land requirements, integrated PV (sometimes also referred to as “PV everywhere”) is of growing interest through functionalizing existing surfaces (roofs, facades, floors, vehicles,...) to make them energy-generating. Such an approach however, may result in non-ideal conditions in terms of temperature (cooling) and exposure to (sun)light due to close-by objects, both static and dynamic.

This topic advances the understanding of partial shading effects in state-of-the-art and next-generation PV modules, a critical factor limiting energy yield and reliability in real-world installations. PV module technology development—optimized cell layouts, interconnection strategies, and advanced encapsulation— enables the design of shade-tolerant modules that maximize performance under non-ideal conditions, backed by advanced modelling of shading behaviour to allow precise assessment of its impact on energy output. Apart from maximizing performance, the simulations and experiments will also provide insights into module reliability and safety related to partial shading (as hotspot formation, degradation, and reverse-bias phenomena), crucial for a successful and widespread adoption of integrated PV inside our societies. The assessment of shade tolerance is also extended to next-generation PV technologies based on tandems with various architectures (2-, 3- and 4-terminal) in order to quantify the impact on energy yield under realistic shading conditions.

Required background: Electrical/Mechanical Engineering, Electrical (Device) Modeling

Type of work: 40% experimental, 40% modeling, 20% literature

Supervisor: Jef Poortmans

Co-supervisor: Patrizio Manganiello

Daily advisor: Jonathan Govaerts

The reference code for this position is 2026-190. Mention this reference code on your application form.

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