MATLAB-BASED OPTIMIZATION OF METHANE FEED INTAKE IN A GTL PLANT FOR SYNTHETIC FUEL PRODUCTION
DOI:
https://doi.org/10.5281/zenodo.19054390Keywords:
Gas-to-Liquids (GTL); Methane feed optimization; multi-objective optimization; Genetic algorithm; Fischer– Tropsch synthesis; Exergy analysis; Syngas production; Nonlinear reactor modeling; Process intensification; Energy efficiency.Abstract
Optimization of methane feed intake plays a critical yet underexplored role in improving the thermodynamic
and economic performance of Gas-to-Liquids (GTL) plants. While previous studies primarily focused on catalyst
development and reactor temperature optimization, the methane intake rate itself has rarely been treated as a primary
decision variable within an integrated kinetic–thermodynamic framework. In this study, a comprehensive nonlinear model
of a GTL plant was developed, integrating methane reforming kinetics, mass and energy balances, Fischer–Tropsch
synthesis reactor performance, and exergy analysis. The reforming section was described using Langmuir–Hinshelwood
kinetics, coupled with plug flow reactor mass–energy balances. A multi-objective optimization problem was formulated
to simultaneously maximize synthetic fuel yield and minimize specific energy consumption, CO₂ emissions, and exergy
destruction. The optimization was solved using a Multi-Objective Genetic Algorithm implemented in MATLAB. Pareto
front analysis revealed a narrow optimal methane intake window between 115 and 132 kmol/h. Within this region, fuel
yield increased by 8.9%, specific energy consumption decreased by 6.1%, CO₂ emissions were reduced by 8.1%, and
total exergy destruction decreased by 9.2% compared to baseline operation. Sensitivity analysis confirmed methane feed
rate as the dominant operational variable, contributing over 40% of total performance variance. Excess methane intake
(>140 kmol/h) was shown to increase thermal irreversibility and oxygen demand with marginal productivity gains, while
insufficient feed (<105 kmol/h) resulted in reactor underutilization. The developed framework demonstrates that methane
intake control represents a powerful and industrially viable optimization lever for GTL plants. The proposed methodology
can be integrated into advanced process control and digital twin platforms to enhance plant efficiency, reduce carbon
footprint, and improve operational stability.
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