期刊
APPLIED ENERGY
卷 178, 期 -, 页码 505-526出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2016.06.060
关键词
Allam cycle; NET power cycle; Oxy-combustion; CO2 capture and storage; Supercritical CO2 cycle; Numerical optimization
资金
- LEAP (Laboratorio Energia Ambiente Piacenza)
This paper presents a thorough thermodynamic analysis and optimization of the NET Power cycle (also called Allam cycle), a natural-gas-fired oxy-combustion cycle featuring nearly 100% CO2 capture level, very high net electric efficiency, and potentially near-zero emissions level. The main goals of this study are the systematic optimization of the cycle for the maximum efficiency, and the quantification of the effects of the modelling assumptions and equipment performance on the optimal cycle variables and efficiency. An Aspen Plus flow-sheet featuring accurate first-principle models of the main equipment units (including cooled turbine) and fluid properties (equation of state) has been developed. The influence of the cycle variables on the thermodynamic performance of the cycle is first assessed by means of sensitivity analyses. Then, the cycle variables, which maximize the net electric efficiency, are determined with PGS-COM, a black-box numerical optimization algorithm, linked to the simulation software. The corresponding maximum cycle efficiency is equal to 54.80% (with 100% CO2 capture), confirming the outstanding performance of the NET Power cycle. Moreover, the optimization indicates the existence of promising combinations of the cycle variables which lead to reduced component costs (due to the lower operating pressures and temperatures) of the most critical components, without considerably affecting the net electric efficiency. The analysis also indicates that the cooling medium temperature, the power consumption of the air separation unit, the effectiveness of the regenerator and the effectiveness of the turbine cooling system are the main factors influencing the cycle efficiency. (C) 2016 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据