Second-law analysis of nanofluid-based photovoltaic/thermal system modeling and forecasting model based on artificial neural network

Abstract

The PVT solar collectors can produce the thermal energy and power in a same frame. The improvement of the PVT's efficiency leads to reducing the system size and capital costs. To this end, this paper studied the irreversibilities of the Al2O3Cu/water hybrid nanofluid (NF) in a PVT solar collector considering two single and double serpentine channels (SS and DS). The influences of Re and nanoparticle concentration (φ) on the thermal and frictional entropy generation rates (S˙th and S˙fr) were investigated and the thermal, electrical and overall exergy efficiencies (ψth, ψe, ψov) of the PVT with SS and DS channels were compared and discussed. Based on the results, the DS channel exhibited S˙fr of almost 75 % lower than SS channel due to lower nanofluid inlet velocities and velocity gradients. In addition, S˙th for the DS channel is nearly 65 % lower and 26 % higher than that for the SS channel at Re numbers of 500 and 2000, respectively. Besides, the Re escalation from 500 to 2000 intensifies S˙fr by almost 94 % at different φs in the SS and DS channels. The increase in φ from 0 % to 1 % escalates S˙fr by almost 99.98 % times for two configuration regardless of the Re number. ψth of the DD channel is nearly 14.5 % and 12.77 % higher than that of the SS channel at Res of 500 and 2000, respectively. Besides, ψe of the PVT with the DS channel is 2.36 % higher than that with SS channel at Re=500 at four studied φs. Moreover, the maximum ψe for the PVT with the DS and SS were obtained as 22.29 % and 21.28 %, respectively, which are associated with Re=1500 and φ=0.25 %. Additionally, a predictive model was presented to determine the total entropy generation rate based in the Re and φ as the inputs.