基于自适应粒子群算法的燃煤-捕碳机组热力系统优化设计  

Optimized Design for Thermodynamic System of Coal-fired Power Plants with CO_2 Capture Based on AWPSO Algorithm

作　　者：付文锋[1] 侯艳峰[1] 王蓝婧[2] 李嘉华[1] 杨勇平[1] 

机构地区：[1]华北电力大学电站设备状态监测与控制教育部重点实验室,河北保定071003 [2]华北电力大学控制与计算机工程学院,河北保定071003

出　　处：《动力工程学报》2016年第9期746-752,共7页Journal of Chinese Society of Power Engineering

基　　金：国家自然科学基金煤炭联合基金资助项目(U1261210);中央高校基本科研业务费专项资金资助项目(2014MS109;2014MS135)

摘　　要：以某1 000 MW超超临界燃煤机组为例,提出了一种新型燃煤-捕碳机组热力系统设计方案,建立了该方案下机组的热经济性计算框架及回热系统参数优化模型,并引入自适应粒子群算法进行优化计算.结果表明:新设计燃煤-捕碳机组的热经济性显著改善,循环热效率比捕碳改造机组相对提高10.7%;自适应粒子群算法收敛快、稳定性好,其优化结果明显优于其他方法,能够适用于燃煤-捕碳机组的热力系统优化设计.Taking the 1 000 MW ultra-supercritical coal-fired unit as an example, a new design scheme was proposed for the thermal system of power plant with CO2 capture, based on which a computing framework for the thermal efficiency and a parameter optimization model for the regenerative system were set up, while the adaptive weighted particle swarm optimization （AWPSO） algorithm was applied for relevant cal- culations. Results show that the thermal economy of the newly-designed coal-fired power unit with CO2 capture has been significantly improved, with its cycle thermal efficiency 10.7% higher than the retrofitted unit before optimization. The AWPSO algorithm is characterized by quick convergence and high stability, and its optimization results are obviously better than other methods, which therefore may be used for de- sign optimization on thermodynamic system of coal-fired carbon-captured power units.

关 键 词：燃煤-捕碳机组 热力系统 自适应粒子群算法 优化设计 

分 类 号：TK284.1[动力工程及工程热物理—动力机械及工程]