The study, published in Energy Conversion and Management, addresses the variability in PDRC performance due to local atmospheric conditions and non-standard experimental configurations. The developed model couples wavelength-dependent material optical properties and sky emissivities derived from libRadtran using real atmospheric data.
Validation against outdoor measurements of nanoporous anodic aluminum oxide and cellulose-based radiative coolers under Madrid summer conditions shows a normalized mean bias error within ± 10% and a coefficient of variation of the root mean square error below 11%, fulfilling ASHRAE Guideline 14–2014.
Parametric studies reveal that geometric and design parameters dominate over atmospheric variations, with temperature differences up to 25 °C compared to approximately 0.2 °C for realistic humidity and temperature variations. Peak daytime net cooling powers reach around 120 W·m−2. The model also includes cloudy conditions, reducing daily cooling power by 26% with a cloud optical depth of 1.
This framework facilitates PDRC climate-specific optimization and supports benchmarking for real-world applications. An initial benchmarking framework is introduced to mitigate historical discrepancies in outdoor PDRC characterization, laying the foundation for developing digital twins of PDRC systems and bridging the gap between nanoscale material properties and macroscale building energy simulations.
