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 language | English |
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| Publication date | Aug 2021 |
| Publication status | Published - Aug 2021 |
| Event | The 2nd International Conference on Energy and AI - London, United Kingdom Duration: 9 Aug 2021 → 13 Aug 2021 |
Conference
| Conference | The 2nd International Conference on Energy and AI |
|---|---|
| Country/Territory | United Kingdom |
| City | London |
| Period | 09/08/2021 → 13/08/2021 |
Keywords
- Power-to-methanol
- Dynamic simulation
- Surrogate modeling
- CO2 hydrogenation
- Methanol synthesis
- Nonlinear autoregressive exogenous model
