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Optimization of a Natural Gas Power Plant with Membrane and Solid Sorbent Carbon Capture Systems
- Source :
- Carbon Capture Science & Technology, Vol 10, Iss , Pp 100165- (2024)
- Publication Year :
- 2024
- Publisher :
- Elsevier, 2024.
-
Abstract
- Carbon capture & storage (CCS) with high capture rates (90-99%) will be necessary to keep natural gas around in a low-carbon future. Furthermore, as intermittent renewable energy expands, natural gas power plants will have to operate at low-load conditions more frequently. To meet these demands, we propose a natural gas combined cycle (NGCC) power plant with a hybrid CCS system that can attain high capture rates and easily cycle between high-load and low-load conditions. More specifically, we propose an integrated system where natural gas exhaust is first processed by a membrane CCS system and then by a solid sorbent CCS system. We integrated models of an NGCC plant, a membrane carbon capture system and a solid sorbent carbon capture system into a single optimization platform to maximize the net present value (NPV) and carbon capture rate of the integrated system. The optimization results indicate a 99.3% carbon capture rate from the inlet natural gas stream at high-load conditions, and a 99.6% carbon capture rate from the inlet natural gas stream at low-load conditions. Compared to a baseline NGCC system without carbon capture, the integrated system has a higher NPV, which indicates that performing carbon capture is more profitable than operating an NGCC system without carbon capture in a future with CO2 taxes. Compared to a baseline NGCC system with an amine-based CCS system that performs 90.7% carbon capture, the proposed integrated system captures more carbon and emits less CO2, while still maintaining a competitive CO2 capture cost.
Details
- Language :
- English
- ISSN :
- 27726568
- Volume :
- 10
- Issue :
- 100165-
- Database :
- Directory of Open Access Journals
- Journal :
- Carbon Capture Science & Technology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.0361796a3a7a4fc5a27de047bc0857f4
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.ccst.2023.100165