Thermodynamic analysis and numerical optimization of a coal-based Allam cycle with full water quench syngas cooling

被引:5
|
作者
Xu, Hongyu [1 ]
Xu, Cheng [1 ]
Guo, Hao [1 ]
Li, Ruifan [1 ]
Xin, Tuantuan [1 ]
Yang, Yongping [1 ]
机构
[1] North China Elect Power Univ, Key Lab Power Stn Energy Transfer Convers & Syst, Minist Educ, Beijing 102206, Peoples R China
关键词
Allam cycle; Carbon capture; Coal gasification; Numerical optimization; Supercritical CO 2 cycle; HIGH-EFFICIENCY; POWER CYCLE; EMISSIONS; ENERGY;
D O I
10.1016/j.enconman.2023.117716
中图分类号
O414.1 [热力学];
学科分类号
摘要
The coal-based Allam cycle is an efficient oxy-fuel combustion semi-closed supercritical carbon dioxide (sCO2) cycle coupled to coal gasification and stands out for its capability to achieve zero carbon emissions. The main goals of this study are to systematically optimize the cycle employing full water quench syngas cooling for maximum efficiency. Detailed analytical models based on energy and material balance are developed to assess the thermodynamic performance of the system. The influences of cycle variables are evaluated through sensi-tivity analyses, and the optimal parameters are determined using a combined black box and PSO-GA approach. Results show that the turbine inlet temperature is the main factor influencing the net cycle efficiency, while higher efficiency is achieved at a relatively low turbine inlet temperature with the increased recovery of syngas heat; the maximum cycle efficiency of the conventional cycle layout is equal to 40.04 %, featuring the turbine inlet temperature of 1031.7 degrees C and pressure of 268.9 bar. Furthermore, an improved cycle with a simplified heat integration process is proposed, featuring a higher net efficiency of 40.22 % and specific work of 252.7 kJ/kg, which demonstrates that the adoption of adiabatic compression in the air separation unit (ASU) is a non-essential measure for efficiency improvement. This study indicates that the availability and grade of syngas heat play a pivotal role in determining the optimal parameters.
引用
收藏
页数:13
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