• Two new reports from the International Energy Agency Photovoltaic Power Systems Programme (IEA PVPS) discuss how performance and reliability of PV power systems can be improved
  • One report, titled Uncertainties in PV System Yield Predictions and Assessments, proposes a method to assess the impact of technical risks on the economic performance of a PV project
  • The other report, titled Review on Infrared and Electroluminescence Imaging for PV Field Applications, recommends ways to use IR and EL imaging techniques to identify and assess specific failure modes of PV modules and systems in field applications

The International Energy Agency Photovoltaic Power Systems Programme (IEA PVPS) has published 2 new reports that look at the performance and reliability of PV systems. These reports are part of the Task 13, which focuses on research covering performance and quality issues. The new reports are published with a view to improve operation, reliability and the electrical and economic output of PV power systems and subsystems.

Any long-term investment in PV power plants calls for long-term yield predictions (LTYP). Research into LTYP is prepared through PV system modelling. This IEA PVPS report collects insights on the uncertainties of several technical aspects of PV system yield prediction and assessment.

It takes into account the uncertainties related to some of the most important measurands in PV performance, including solar resources, module properties and system output. The report also investigates some modelling steps for gains and losses in a PV system comprising the same factors.

The report proposes a method that aims to assess the impact of technical risks on the economic performance of a PV project. The authors have proposed this method in an attempt to standardize the procedure of calculating energy yields of PV systems to estimate financial investment risk.

The other new report published by Task 13 covers the current practice for infrared (IR) and electroluminescence (EL) imaging of PV modules and systems. Taking environmental and device requirements into consideration, it also interprets sample patterns with abnormalities. The report recommends guidelines for using IR and EL imaging techniques to identify and assess specific failure modes of PV modules and systems in field applications.

Furthermore, it offers guidance for preventive maintenance and fault diagnostics of PV plants through IR imaging techniques while the plant is operating under natural sunlight. It also describes the types of cameras used for EL imaging and discusses sensors. The report ultimately suggests a combination of both techniques to quickly detect most defects in a PV module with a high level of accuracy.