Nowadays, optimization of photovoltaic (PV) modules and systems operating conditions purely rely on electrical information. Continuous tracking of the electrical operating point is performed in order to maximize energy production. However, such a limited amount of cumulative information does not allow for optimal exploitation of PV modules potential, since non-uniformities within PV modules are not detected, nor for detection of unwanted operating conditions, such as partial shading, soiling and local overheating, nor for identification of degradation and faults, e.g. local cell damages. As a matter of fact, PV systems keep working sub-optimally until losses are big enough to ring a warning bell. Or, PV modules are checked from time to time by drones and operators for signs of degradation and faults. This approach leads to two main disadvantages: late detection of degradation and faults, with the consequence of lower power production and shorter PV module lifetime, and increase of operation and maintenance cost.
Ideally, electrical information should be accompanied by thermal and optical information along the PV module surface: knowledge of cells' operating temperature and irradiation levels will provide a picture of the current status of the PV module. For instance, partial shading and soiling would entail non-uniform distribution of irradiation, whereas local damages would lead to significant local overheating.
Thin-film electronics represents a relevant and promising solution to the issues presented above. Thin-film devices and circuits can be realized on a foil, then laminated within the PV module, allowing embedment of distributed sensors within the PV module itself. This represents the best way to get access to such distributed information, opening the path towards the realization of a new generation of intelligent and self-aware PV modules. The goal of this Ph.D. is to demonstrate the feasibility and the added values of the proposed approach, through small-scale demonstrators at first and full-scale PV modules at last. The Ph.D. candidate will work on technology selection, circuit design, definition of location, type and number of sensors needed to properly control and identify PV module's operating conditions and state of health, as well as on the physical integration of thin-film electronics on foil in the PV module laminate.
Required background: Engineering Technology, Engineering Science
Location: This position will be partly at the site of EnergyVille, where you will have direct access to PV module assembly laboratories, outdoor measurement sites, and experts working on PV modules and systems R&D, and partly at the site of Leuven, where the activities on thin-film electroncs are located and you work in imec's and KULeuven state-of-art labs.
Type of work: 10% analysis of PV-related constraints for thin-film electronics integration, 20% research on PV degradation signatures, 40% research on thin-film technology, 30% experiments
Supervisor: Jan Genoe
Daily advisor: Patrizio Manganiello, Kris Myny
The reference code for this position is 2020-070. Mention this reference code on your application form.
Chinese nationals who wish to apply for the CSC scholarship, should use the following code when applying for this topic: CSC2020-32.