Solar drying for different test conditions: Proposed framework for estimation of specific energy consumption and CO2 emissions mitigation

In the present study, drying experiments on mixed-mode solar dryer with cylindrical potato samples have been performed for a wide range of process variables. The variables investigated are absorbed thermal energy, air flow rate, food product loading density and sample thickness. A mathematical framework is developed to estimate several dryer performance indicators namely: drying efficiency, SEC (specific energy consumption), CO2 emissions mitigation, carbon credits earned and amount of different fossil fuels saved due to use of solar drying. The fossil fuels investigated in the present study are coal, diesel, natural gas and LPG (liquefied petroleum gas). The results of investigation indicate that for all drying test conditions, the given dryer is capable to mitigate the maximum CO2 emissions with the replacement of coal by solar energy. Larger values of absorbed energy and load density cause increased SEC and CO2 mitigation potential whereas reverse trend is observed for sample thickness. However, the influence of air flow rate on these parameters is found to be quite different. In order to establish functional relationship between SEC and process variables, a correlation is developed using Levenberg–Marquart algorithm. The statistical error analysis reveals that the proposed correlation is capable of satisfactory prediction of experimental results.