"A novel approach for the modelling of convective phenomena for building integrated photovoltaic thermal (BIPV/T) systems". (15th January 2022) - Dimitrios Rounis, Efstratios; Ioannidis, Zisis; Sigounis, Anna-Maria; Athienitis, Andreas; Stathopoulos, Theodore
Highlights: Novel approach for modelling of convective phenomena for air-based BIPV/T. Wind-driven and channel flow-driven convection treated as interlinked phenomena. Comparison of different modelling approaches for BIPV/T. Experimental investigation of thermal performance parameters for BIPV/T. Applications for control and system performance comparison. Abstract: This study introduces a novel approach for the modelling of convective phenomena for air-based building integrated photovoltaic thermal (BIPV/T) systems, which takes into consideration the interlinked nature of wind-driven and channel flow-driven convective phenomena. Expressions for wind-driven and channel convection used in the respective literature, tend to be case specific, while predictions for air temperature rise have been found to differ by >10 °C from monitored values, resulting in poor thermal utilization and cooling of the PV panels. In this paper, the key parameters affecting the thermal performance of a BIPV/T system, have been formulated into dimensionless groups and correlated to the ratio of wind-driven convective heat transfer to the system heat recovery. This correlation was verified experimentally through testing in a full-scale solar simulator. Air temperature rise predictions from the proposed modelling approach showed good agreement with the experimental results, with an R 2 of 0.93. The proposed methodology can be tailored to individual systems and climates via calibration through key temperatures monitoring and can be instrumental in the optimal control and heat utilization for a coupled BIPV/T-HVAC system. In addition, it can yield increased durability and performance of the PV installation through incorporation of more efficient cooling strategies, through accurate outlet air temperature and PV temperature predictions, respectively.