Publications by authors named "Andreas Livera"
Article Synopsis
- Long-term stability poses a significant challenge for commercializing perovskite solar cells, made worse by a lack of consistent outdoor testing data.
- This study involved two years of outdoor testing on perovskite mini-modules, analyzing their performance changes throughout each day, including both degradation during the day and recovery overnight.
- Using the XGBoost regression model, the researchers successfully predicted the power output of the mini-modules, achieving a low error rate, which shows promise for estimating the lifespan of perovskite devices based on environmental factors.
Accurate photovoltaic (PV) diagnosis is of paramount importance for reducing investment risk and increasing the bankability of the PV technology. The application of fault diagnostic solutions and troubleshooting on operating PV power plants is vital for ensuring optimal energy harvesting, increased power generation production and optimised field operation and maintenance (O&M) activities. This study aims to give an overview of the existing approaches for PV plant diagnosis, focusing on unmanned aerial vehicle (UAV)-based approaches, that can support PV plant diagnostics using imaging techniques and data-driven analytics.
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