基于改进多种群遗传算法的核电热力系统参数优化  

Optimization of Nuclear Power Thermal System Parameters Based on Improved Multi-population Genetic Algorithm

作　　者：鹿纯彬 邢天阳 朱小良[1] 胥建群[1] LU Chun-bin;XING Tian-yang;ZHU Xiao-liang;XU Jian-qun(School of Energy and Environment,Southeast University,Nanjing 210096,China)

机构地区：[1]东南大学能源与环境学院,南京210096

出　　处：《汽轮机技术》2024年第3期212-216,共5页Turbine Technology

摘　　要：核电机组二回路热力系统是将热能转化为机械能并进行发电的关键部分,在保证安全的基础上提高其效率具有重要意义。对此,首先根据热平衡法建立热力系统的数学模型。其次,在多种群遗传算法的基础上增加并行机制与协同策略,结合自适应策略提出一种改进多种群遗传算法,并利用测试函数测试其寻优性能。最后,以机组循环热效率为目标函数,回热再热抽汽流量为决策变量,在约束条件下采用改进算法对热力系统进行优化设计。结果表明:改进多种群遗传算法比标准遗传算法与多种群遗传算法更有效率且收敛精度高;采用该优化算法后,机组循环热效率提高了1.18%。The two-loop thermal system of a nuclear power unit is the key part that converts thermal energy into mechanical energy and generates electricity,and it is of great significance to improve its efficiency on the basis of ensuring safety.In this regard,firstly,a mathematical model of the thermal system is established based on the heat balance method.Secondly,an improved multi-population genetic algorithm is proposed on the basis of multi-population genetic algorithm by adding parallel mechanism and collaborative strategy and combining with adaptive strategy,and its optimization-seeking performance is tested by using test function.Finally,the improved algorithm is used to optimize the thermal system under the constraints with the thermal efficiency of the unit cycle as the objective function and the return heat and reheat steam flow rate as the decision variable.The results show that the improved multi-population genetic algorithm is more efficient and has higher convergence accuracy than the standard genetic algorithm with multi-population genetic algorithm;the thermal efficiency of the unit cycle is improved by 1.18%.

关 键 词：核电热力系统 改进式多种群遗传算法 参数优化 循环热效率 

分 类 号：TL48[核科学技术—核技术及应用]