Sascha Lindig works as a researcher at EURAC in Bolzano/Italy, where he is currently completing his doctorate in cooperation with the University of Ljubljana/Slovenia as part of the H2020 Marie-Sklodowska-Curie Solar-Train project. His studies focus on statistical models for the quantification of the degradation of PV systems, degradation patterns and the economic evaluation of technical failures in PV systems. He first studied photovoltaic and semiconductor technologies at the University of Applied Sciences in Jena/Germany and then environmental and energy technologies at the HTWK Leipzig/Germany, where he received his Master of Engineering in 2014.
03:15 pm - 03:35 pm
In future, big data analysis using advanced AI techniques based on the monitoring of a large amount of data will enable the development of extensive benchmarking of key performance indicators (KPIs) for the solar PV industry. This will help PV developers to derive the real-life impact on the system losses and reliability of design choices and configuration during design phase, while O&M operators could optimize their maintenance routines during the operational phase. The presentations in session 2 will cover the outcomes of the work carried out by IEA PVPS Task 13 experts to provide best practice on how to gain insights from monitored data and extreme diversity of asset types and operational context within a PV plant.
This session is jointly organized by Intersolar and IEA PVPS Task 13.