Optimizing syngas production for enhanced gas turbine power generation: A thermodynamic and feedstock analysis

As the demand for alternative and renewable energy solutions increases, particularly in developing nations facing unreliable power supply, optimizing biomass gasification processes for power generation has become a critical challenge. Syngas, composed primarily of carbon monoxide (CO), hydrogen (H₂), and carbon dioxide (CO₂), plays a pivotal role in driving gas turbine power generation. However, the impact of varying feedstock types, thermodynamic conditions, and syngas quality on power output is still not well understood. This study addresses this knowledge gap by investigating the effects of feedstock composition (C1 to C4 alkanes), temperature, and pressure on syngas production and gas turbine efficiency. Using process simulations with DWSim and optimization techniques such as response surface methodology (RSM), we identify optimal syngas compositions for maximizing gas turbine duty (GTD). The results demonstrate that a balanced syngas mixture (CO = 4 kmol/h, H₂ = 4 kmol/h, CO₂ = 4 kmol/h) yields a GTD of 48.2 kW, significantly enhancing power generation efficiency. Our findings underscore the critical role of CO₂ in stabilizing combustion, improving thermal efficiency, and ensuring stable turbine operation, while CO and H₂ contribute directly to the energy conversion process. This research provides valuable insights for optimizing bioenergy systems, offering predictive models that can guide the development of more efficient and sustainable biomass-based power generation technologies.