Investigation of optimum H2 production from date palm waste leaves using different modeling tools

Abstract

Globally, the productive utilization of biomass has paid serious attention to fulfilling the energy requirements laid out by the international standards, as to reduce related carbon footprints. Therefore, this study investigates date palm waste leaves which aims to produce environment friendly H2 gas using gasification technology. The results of 25 experimental runs exhibited that the higher H2 produced at higher temperature which was mainly supported by water-gas-shift and steam-methane reforming reactions. H2 prediction was modeled using response surface methodology (RSM) and artificial neural network (ANN). The RSM model exhibited a strong interaction with the regression coefficient (R2) and p-value of 0.89 and 0.000000, respectively. ANN data was disseminated thru K-fold contrivance with back-propagation algorithm. Hence, the training (80% data) and validation (20% data) datasets were found with R2 and root mean squared error (RSME) of 0.90 and 0.28, and 0.86 and 0.39, respectively. Kinetics of the process estimated the activation energies (Ea) using Ozawa-Flynn-Wall (OFW), Starink (STK), and Kissinger-Akahira-Sunose (KAS) models. Hence, the values of Ea and R2 at conversion degrees (α) 0.1 to 0.8 were ranged between 129.40 and 326.64 kJ/mol and 0.92 to 0.97, respectively. Optimum H2 production of 49.03 vol% (with LHV of 11.10 MJ/Nm3) was produced. This finding is thought to be a better source of energy which can be an appropriate fuel for Fischer Tropsch process for manufacturing of transportation fuels.