Exergy Analysis of Biomass and Solar Based Methanol Synthesis System


Dincer M. M., Kuran B., Kirkar M.

14th International Conference on Renewable Energy Research and Applications, ICRERA 2025, Vienna, Austria, 27 - 30 October 2025, pp.317-319, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icrera66237.2025.11283831
  • City: Vienna
  • Country: Austria
  • Page Numbers: pp.317-319
  • Keywords: Artificial Neural Network, efficiency, energy, exergy, methanol
  • Yıldız Technical University Affiliated: Yes

Abstract

In this study, a biomass gasification system is combined with a solar tower-assisted methanol synthesis system, and the thermodynamic evaluation of the combined system is presented. In this study, a biomass gasification system is combined with a solar tower-assisted methanol synthesis system, and the thermodynamic evaluation of the combined system is presented. The exergy and energy performances of this system are analyzed by Aspen Plus software. Sensitivity analyses are utilized to determine the effect of gasification temperature and steam-tobiomass ratio on the composition of the rates of syngas and the rates of methane, methanol, and hydrogen generation. The results disclose that overall exergy efficiency is 66% and overall energy efficiency is 46% for the designed system. To optimize the system parameters, the Radial Basis Function Neural Network technique is utilized. Steam-to-biomass ratio-based forecasts for methane production attain the lowest error metrics.