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Multi-objective genetic algorithm approach for enhanced cumulative hydrogen and methane-rich syngas emission through co-pyrolysis of de-oiled microalgae and coal blending

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  • Rawat, Shweta
  • Wagadre, Lokesh
  • Kumar, Sanjay

Abstract

Towards establishing low-carbon bio-economy, the energy-rich syngas is considered a global energy carrier. Targeting hydrogen as a promising advanced fuel, the significance of methane also increases due to its direct conversion capability into hydrogen. The current study aims to use a co-pyrolysis-based valorization of de-oiled microalgae and low-rank coal blend to generate H2 and CH4 rich syngas. Pyrolysis kinetic models, Kissinger-Akahira-Sunose (KAS) and Starink (STK) are used to evaluate apparent activation energy (Ea). The gradual addition of microalgae (0⎼100%) in coal reduces Ea from 189.11⎼55.87 kJ/mol and 180.16⎼54.61 kJ/mol by KAS and STK method, respectively. The maximum hymethane carrying ratio is observed 2.51 and 3.51 at optimized conditions of response surface methodology (RSM) and artificial neural network-based multi-objective genetic algorithm (ANN-MOGA), respectively. Maximum H2 (54.5 %) in the syngas is observed at mid pyrolysis stage (451 °C) using ANN-MOGA optimized conditions (blending ratio - 42.25 % and heating rate-13.8 °C/min). This study highlights the advantage of ANN-MOGA optimization over statistical based optimization. Hence, incorporating of the evolutionary algorithm as integrated ANN-MOGA optimization could be an efficient way for hymethane rich syngas emission in co-pyrolysis approach to gain carbon-neutral energy with zero waste discharge.

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  • Rawat, Shweta & Wagadre, Lokesh & Kumar, Sanjay, 2024. "Multi-objective genetic algorithm approach for enhanced cumulative hydrogen and methane-rich syngas emission through co-pyrolysis of de-oiled microalgae and coal blending," Renewable Energy, Elsevier, vol. 225(C).
    • Handle: RePEc:eee:renene:v:225:y:2024:i:c:s096014812400329x
    DOI: 10.1016/j.renene.2024.120264
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    References listed on IDEAS

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