THE FEED GAS COMPOSITION EFFECTS ON THE GREEN METHANOL PRODUCTION: DYNAMIC SIMULATION AND SURROGATE MODELING

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Abstract

Power-to-methanol is seen as a key energy storage technology in contributing to reach climate targets and unleash the great potential for renewable electricity. This study conducted dynamic simulations that focuses on the feed gas composition effects and surrogate modeling by using the nonlinear autoregressive exogenous (NARX) model for the green methanol production. The modeling results showed obvious influences of feed gas composition on the process efficiency and CO2 conversion, which were predicted by the NARX model with promising accuracy.
Original languageEnglish
Publication dateAug 2021
Publication statusPublished - Aug 2021
EventThe 2nd International Conference on Energy and AI - London, United Kingdom
Duration: 9 Aug 202113 Aug 2021

Conference

ConferenceThe 2nd International Conference on Energy and AI
Country/TerritoryUnited Kingdom
CityLondon
Period09/08/202113/08/2021

Keywords

  • Power-to-methanol
  • Dynamic simulation
  • Surrogate modeling
  • CO2 hydrogenation
  • Methanol synthesis
  • Nonlinear autoregressive exogenous model

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