Optimisation of syngas composition for emissions minimisation and cost reduction through selective catalytic reduction (SCR) and gas mixtures in a gas turbine
Optimisation of syngas composition for emissions minimisation and cost reduction through selective catalytic reduction (SCR) and gas mixtures in a gas turbine
The fuel flexibility of a gas turbine allows it to operate on a large variety of fuels, with syngas gaining prominence in recent years due to its versatility to be produced from any hydrocarbon-based feedstock. The feedstock versatility also meant that the syngas produced could be hydrogen-rich or carbon monoxide-rich in its composition. In this experimental study, the emissions characteristics of syngas combustion in a gas turbine, and their associated cost to minimise emissions using the selective catalytic reduction (SCR) method and gas mixtures were investigated. The syngas composition comprised of four gases, namely H2, CO, CO2 and CH4. The syngas mixture is combusted under an equivalence ratio (ER) range of 0.4-0.9. Using Design of Experiments (DOE) optimisation procedures for simultaneous NOx-CO reduction, the emission indices of the NOx and CO pollutants for the best H2-rich syngas (ER=0.5) were found to be 0.0189 g/kWh and 0.0028 g/kWh lower than that of the optimum CO-rich syngas (ER=0.5), respectively. This implies that H2-rich syngas has greater potential for emissions reduction. However, the general combined costs for an optimum H2-rich syngas mixture with the SCR post-treatment method is about six folds greater than the CO-rich syngas counterparts. The actual cost is even greater on a cost per mass reduction basis, with the NOx and CO emissions being 21.6 and 8.9 times more for the H2-rich mixture. It was also determined that the combined use of SCR method and optimum gas mixture is a more cost-effective emissions control measure than purely using direct gas mixture.
Jo-Han, Ng
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Xian Lim, Zi
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Yao Wong, Kang
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Tung Chong, Cheng
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Jo-Han, Ng
4c9c51bd-1cfc-46c0-b519-23b77566fe50
Xian Lim, Zi
c6938ab0-251d-4216-a5ab-de29e6c7d29a
Yao Wong, Kang
7bbce6ab-89b5-4b6c-ab92-d853735a505b
Tung Chong, Cheng
a3b41f14-a280-47e8-a7db-2d8641fbcabc
[Unknown type: UNSPECIFIED]
Abstract
The fuel flexibility of a gas turbine allows it to operate on a large variety of fuels, with syngas gaining prominence in recent years due to its versatility to be produced from any hydrocarbon-based feedstock. The feedstock versatility also meant that the syngas produced could be hydrogen-rich or carbon monoxide-rich in its composition. In this experimental study, the emissions characteristics of syngas combustion in a gas turbine, and their associated cost to minimise emissions using the selective catalytic reduction (SCR) method and gas mixtures were investigated. The syngas composition comprised of four gases, namely H2, CO, CO2 and CH4. The syngas mixture is combusted under an equivalence ratio (ER) range of 0.4-0.9. Using Design of Experiments (DOE) optimisation procedures for simultaneous NOx-CO reduction, the emission indices of the NOx and CO pollutants for the best H2-rich syngas (ER=0.5) were found to be 0.0189 g/kWh and 0.0028 g/kWh lower than that of the optimum CO-rich syngas (ER=0.5), respectively. This implies that H2-rich syngas has greater potential for emissions reduction. However, the general combined costs for an optimum H2-rich syngas mixture with the SCR post-treatment method is about six folds greater than the CO-rich syngas counterparts. The actual cost is even greater on a cost per mass reduction basis, with the NOx and CO emissions being 21.6 and 8.9 times more for the H2-rich mixture. It was also determined that the combined use of SCR method and optimum gas mixture is a more cost-effective emissions control measure than purely using direct gas mixture.
Text
Jo-Han_2019_IOP_Conf._Ser.__Earth_Environ._Sci._268_012160
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e-pub ahead of print date: 2 July 2019
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International Conference on Sustainable Energy and Green Technology 2018, SEGT 2018, , Kuala Lumpur, Malaysia, 2018-12-11 - 2018-12-14
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Local EPrints ID: 432609
URI: http://eprints.soton.ac.uk/id/eprint/432609
ISSN: 1755-1307
PURE UUID: 43c02e01-5d6e-4be2-b137-5838b06eecab
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Date deposited: 22 Jul 2019 16:30
Last modified: 22 Nov 2021 03:15
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Author:
Zi Xian Lim
Author:
Kang Yao Wong
Author:
Cheng Tung Chong
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