Unveiling the impact of photovoltaic degradation mechanisms

HomeRACE for PhD ProjectsRACE for NetworksUnveiling the impact of photovoltaic degradation mechanisms

Supervisors

Chris Martell (GSES)

Earl Duran (Diagno)

The project

This PhD project addresses a key barrier to reliable, low-cost solar energy: accurately identifying why photovoltaic systems underperform in the field. Current methods often overlook the complex, non-linear nature of degradation due to weather effects and hidden faults. This research will develop a machine learning pipeline to correct for environmental noise, filter out faults, and uncover true degradation trends. By statistically analysing the full distribution of degradation rates, including extreme degradation, it will link observed patterns to physical failure mechanisms. The outcomes will support better module design, smarter maintenance, and stronger investment confidence, directly contributing to our goals of reducing energy costs, cutting emissions, and increasing system reliability.

Status