超临界二氧化碳再压缩布雷顿循环性能分析及优化设计方法研究

Performance Analysis and Optimization Design Method of Supercritical Carbon Dioxide Recompression Brayton Cycle

关键词:  超临界态  二氧化碳  再压缩循环  循环热效率  约束条件  粒子群算法  优化设计方法

Key words:  Supercritical state  Carbon dioxide  Recompression cycle  Cycle thermal efficiency  Constraint  Particle swarm optimization  Optimization design method

摘要:

为发展工程适用的超临界二氧化碳布雷顿循环优化设计方法，研究了关键参数对超临界二氧化碳再压缩循环性能的影响规律，阐述了循环优化设计的必要性，并基于粒子群算法发展了一种再压缩循环优化设计方法。该方法以最低循环压力、循环增压比和分流因子为优化变量，以循环热效率为目标，以合流三通进口温差为约束条件。参数影响规律分析结果表明：循环效率随最低温度的增大持续降低，而随最高温度的增加单调上升；存在最优最低压力和最优增压比使得循环效率最高，且分别受最低温度和最高温度不同程度的影响；将更少的流量分配给再压缩压气机有利于循环效率，且存在最优分流因子使循环效率最高；合流三通进口温差受分流因子影响显著，该参数有必要作为循环设计的限制条件。此外，该循环优化设计方法能有效完成不同温差限制下的循环优化设计，设计结果表明：1℃最大温差下循环效率可达47.77%，而10℃和20℃最大温差下循环效率可达47.83%。

Abstract:

To develop engineering-applicable optimization design method for supercritical carbon dioxide Brayton cycle， analysis of the effects of key parameters on the recompression cycle was firstly carried out， and the necessity for cycle optimization design was elaborated. Then an optimization design method for the recompression cycle was proposed based on the particle swarm optimization algorithm. The minimum cycle pressure， cycle pressure ratio and flow split ratio were selected as optimization variables， with the cycle thermal efficiency considered as objective and inlet temperature difference of the flow-split tee as constraint. Results of parametric analysis show that the cycle thermal efficiency decreases persistently with the minimum temperature increasing， while increases monotonically with the maximum temperature increasing. An optimal minimum pressure and optimal pressure ratio resulting in the highest cycle efficiency are found， and they are effected by the minimum temperature and maximum temperature， respectively. Assigning less massflow to the re-compressor is expected to be beneficial to the cycle efficiency， and there is an optimal flow split ratio which would lead to the highest cycle efficiency. The inlet temperature difference of the flow-split tee is significantly effected by the flow split ratio， and this key parameter should be considered as a constraint for cycle optimization. Besides， the proposed method is capable for cycle optimization design， under different temperature difference constraints. Optimization design results showed that a thermal efficiency of 47.77% could be reached under 1℃ temperature difference， while a thermal efficiency of 47.83% could be reached under 10℃ and 20℃ temperature difference.