化工学报2024，Vol.75Issue(6)：2143-2156,14.DOI:10.11949/0438-1157.20240080
再压缩S-CO2布雷顿循环性能分析及多目标优化
Performance analysis and multi-objective optimization of recompression S-CO2 Brayton cycle
摘要
Abstract
The solar thermal power generation technology combined with heat storage has stable output and strong peak shaving capabilities.The introduction of supercritical carbon dioxide(S-CO2)Brayton cycle can further improve thermoelectric conversion efficiency.Most of the existing studies evaluated the performance of S-CO2 cycle based on a single index,leading to inconsistent evaluation results.Hence,it is necessary to carry out multi-index comprehensive evaluation to objectively reflect the cycle performance.In the present paper,mathematical models were established to investigate the thermodynamic performance and economy of a 35 MW recompression S-CO2 cycle,and the effects of critical parameters on cycle performance was analyzed.A BP-GA optimization method of back propagation neural network combined with elitist nondominated sorting genetic algorithm was constructed for multi-objective optimization of cycle performance.The results indicate that the cycle efficiency increases with an increasing total thermal conductivity of the recuperators,but there is a ceiling on growth.There are significant non-monotonic relations between turbine inlet temperature,minimum cycle pressure,maximum cycle pressure,split ratio and cycle performance,and the corresponding optimal values are 639.14℃,8.10 MPa,29.74 MPa and 0.70,respectively.Compared with the cycle performance based on the design conditions,the optimized cycle shows a reduction of 11.1%in LCOE,and an increase of 5.1%and 27.6%in efficiency and specific work,respectively.关键词
超临界二氧化碳/再压缩布雷顿循环/遗传算法/整体优化/热力学Key words
supercritical carbon dioxide/recompression Brayton cycle/genetic algorithm/global optimization/thermodynamics分类
能源科技引用本文复制引用
李子扬,郑楠,方嘉宾,魏进家..再压缩S-CO2布雷顿循环性能分析及多目标优化[J].化工学报,2024,75(6):2143-2156,14.基金项目
国家自然科学基金项目(52006163) （52006163）
