Techno-economic assessment of integrated power plant with methanation
Greenhouse gaseous (GHG) emissions increment is driven by economic and population growth which are getting higher. This has led to the increase of atmospheric concentration of CO 2. Due to this situation, carbon capture utilisation and storage (CCUS) seems to be promising approach to reduce emission...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Italian Association of Chemical Engineering - AIDIC
2018
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/84425/1/ZarinaAbMuis2018_TechnoeconomicAssessmentofIntegratedPowerPlant.pdf http://eprints.utm.my/id/eprint/84425/ http://dx.doi.org/10.3303/CET1863076 |
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| Summary: | Greenhouse gaseous (GHG) emissions increment is driven by economic and population growth which are getting higher. This has led to the increase of atmospheric concentration of CO 2. Due to this situation, carbon capture utilisation and storage (CCUS) seems to be promising approach to reduce emission of CO 2. Among all the carbon utilisation strategies available, methanation is promising. In the perspective of integrated power plant with methanation, the process is appropriate and relatively simpler due to availability of hydrogen as its main constituent. Prior to the goal of abatement of greenhouse gases emission, hydrogen production by using renewable energy technology which is electrolysis seems to be one of the solution towards future energy security. This study performed a techno economic assessment of integrated power plant with methanation with a case study in Iskandar Malaysia. From the economic assessment results, highest profit is generated when PEM is used in electrolysis process and CIS is used as solar panel due to its high efficiency and low capital expenditure (CAPEX). This cost competitiveness can be enhanced selling O 2 by product produced from electrolysis process and recycling the catalyst for methanation process. Further studies can be extended by including variation of parameter for a better optimisation superstructure. |
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