Prediction of the surface temperature of building-integrated photovoltaics: Development of a high accuracy correlation using computational fluid dynamics

•CFD model of a BIPV model is validated against particle image velocimetry and infrared thermography studies.•A new correlation to predict the surface temperature of the BIPV modules is proposed.•The accuracy and uncertainty of the proposed correlation are investigated.

Building-integrated photovoltaic (BIPV) panels are generally expected to operate for over 25 years to be viewed as an economically viable technology. Overheating is known to be one of the major deficiencies in reaching the targeted lifespan goals. Alongside the thermal degradation, the operational efficiency of the silicon-based solar panel drops when the surface temperature exceeds certain thresholds close to 25 °C. Wind-driven cooling, therefore, is widely recommended to decrease the surface temperature of PV panels using cavity cooling through their rear surfaces. Wind-driven flow can predominantly contribute to cavity cooling if a suitable design for the installation of the BIPV systems is considered.In general, various correlations in the form of Nu=CRea are adapted from heat convection of flat-plates to calculate the heat removal from the BIPV surfaces. However, these correlations demonstrate a high discrepancy with realistic conditions due to a more complex flow around BIPVs in comparison with the flat-plate scenarios. This study offers a significantly more reliable correlation using computational fluid dynamics (CFD) technique to visualize and thus investigate the flow characteristics around and beneath BIPVs. The CFD model is comprehensively validated against a particle velocimetry and a thermography study by Mirzaei et al. (2014) and Mirzaei and Carmeliet (2013b). The velocity field shows a very good agreement with the experimental results while the average surface temperature has a 6.0 % discrepancy in comparison with the thermography study. Unlike the former correlations, the coefficients are not constant numbers, but a function of the airflow velocity, in the newly proposed correlation, which is in the form of NuL=0.1513ReL0.7065.

Graphical abstractThe performance of the newly developed correlation against precedent regressions.Download high-res image (104KB)Download full-size image