New Guidelines for Accurate Benchmarking of Indoor Photovoltaics
Indoor photovoltaics (IPVs) are emerging as a viable solution for powering Internet-of-Things (IoT) devices, prompting increased research and development in this field. However, the diverse lighting conditions used in IPV studies present significant challenges for accurate characterization, reporting, and benchmarking of these technologies. Variations in artificial light sources can obscure genuine performance improvements and lead to erroneous conclusions due to characterization errors.
A recent study conducted by Javith Mohammed Jailani and colleagues provides a comprehensive analysis of these challenges. The research covers a wide range of IPV technologies, including crystalline silicon (c-Si), amorphous silicon (a-Si:H), perovskite, and organic photovoltaics. The authors highlight that many existing methodologies can result in unacceptable levels of error, particularly due to the angular relationships between the light source, measuring device, and IPV device, which can compromise accuracy under diffuse lighting conditions.
To address these issues, the study evaluates practical protocols aimed at overcoming angular discrepancies and enabling benchmarking against standardized spectral conditions. The authors also present detailed checklists designed to facilitate accurate IPV characterization, reporting, and benchmarking.
The findings of this research are expected to stimulate further advancements in IPV technologies by ensuring reliable performance evaluations. This could ultimately help realize the full potential of IPVs in powering smart devices, which is increasingly important in a world that is becoming more reliant on IoT solutions.
For more details, the paper titled "Accurate Performance Characterization, Reporting, and Benchmarking for Indoor Photovoltaics" can be accessed at arXiv:2408.13485. The authors include Javith Mohammed Jailani, Amanda Luu, Elizabeth Salvosa, Charlotte Clegg, Vishnupriya P. Kamalon, Bahareh Nasrollahi, Irina Valitova, Sebastian B. Meier, Andrew M. Shore, Behrang H. Hamadani, and Vincenzo Pecunia.