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

Xiaoti Cui; Søren Knudsen Kær; Mads Pagh Nielsen

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

Xiaoti Cui, Søren Knudsen Kær, Mads Pagh Nielsen

Publikation: Konferencebidrag uden forlag/tidsskrift › Konferenceabstrakt til konference › Forskning › peer review

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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.

Originalsprog	Engelsk
Publikationsdato	aug. 2021
Status	Udgivet - aug. 2021
Begivenhed	The 2nd International Conference on Energy and AI - London, Storbritannien Varighed: 9 aug. 2021 → 13 aug. 2021

Konference

Konference	The 2nd International Conference on Energy and AI
Land/Område	Storbritannien
By	London
Periode	09/08/2021 → 13/08/2021

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title = "THE FEED GAS COMPOSITION EFFECTS ON THE GREEN METHANOL PRODUCTION: DYNAMIC SIMULATION AND SURROGATE MODELING",

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.",

keywords = "Power-to-methanol, Dynamic simulation, Surrogate modeling, CO2 hydrogenation, Methanol synthesis, Nonlinear autoregressive exogenous model",

author = "Xiaoti Cui and K{\ae}r, {S{\o}ren Knudsen} and Nielsen, {Mads Pagh}",

year = "2021",

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note = "The 2nd International Conference on Energy and AI ; Conference date: 09-08-2021 Through 13-08-2021",

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THE FEED GAS COMPOSITION EFFECTS ON THE GREEN METHANOL PRODUCTION: DYNAMIC SIMULATION AND SURROGATE MODELING. / Cui, Xiaoti; Kær, Søren Knudsen; Nielsen, Mads Pagh.
2021. Abstract fra The 2nd International Conference on Energy and AI, London, Storbritannien.

Publikation: Konferencebidrag uden forlag/tidsskrift › Konferenceabstrakt til konference › Forskning › peer review

TY - ABST

T1 - THE FEED GAS COMPOSITION EFFECTS ON THE GREEN METHANOL PRODUCTION

T2 - The 2nd International Conference on Energy and AI

AU - Cui, Xiaoti

AU - Kær, Søren Knudsen

AU - Nielsen, Mads Pagh

PY - 2021/8

Y1 - 2021/8

N2 - 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.

AB - 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.

KW - Power-to-methanol

KW - Dynamic simulation

KW - Surrogate modeling

KW - CO2 hydrogenation

KW - Methanol synthesis

KW - Nonlinear autoregressive exogenous model

UR - http://www.energy-ai.org/

M3 - Conference abstract for conference

Y2 - 9 August 2021 through 13 August 2021

ER -

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

Abstract

Konference

FN’s Verdensmål

AUB Link

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