期刊
INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL
卷 10, 期 -, 页码 148-163出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ijggc.2012.06.002
关键词
CO2 capture cost; Mathematical modeling; Optimization NLP models; Greenhouse gas emissions; Post-combustion process
类别
资金
- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET, Argentina)
- Universidad Tecnologica Nacional Facultad Regional Rosario (UTN-FRRo, Argentina)
The post combustion process based on the CO2 absorption using amine aqueous solution is one of the more attractive options to drastically reduce greenhouse gas emissions from electric power sector. However, the solvent regeneration is highly energy intensive affecting the total operating cost significantly. The CO2 removal target depends on the absorption and desorption processes where the main parameters of both processes are strongly coupled. Consequently, the simultaneous optimization of the whole CO2 capture process is essential to determine the best design and operating conditions in order to minimize the total cost. This paper presents and discusses different cost optimizations including both investments and operating costs. The impact of different CO2 emission reduction targets on the total annual cost, operating conditions and dimensions of process units is investigated in detail. Optimized results are discussed through different case studies. (c) 2012 Elsevier Ltd. All rights reserved.
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