小型压水堆核蒸汽供应控制系统参数多目标优化研究  

Research on Multi-objective Optimization of Parameters of Small Pressurized Water Reactor Nuclear Steam Supply Control System

作　　者：李政[1] 陈楚琦 曾文杰[1] 李若鲲 Li Zheng;Chen Chuqi;Zeng Wenjie;Li Ruokun(School of Nuclear Science and Technology,University of South China,Hengyang,Hunan,421001,China;Hainan Nuclear Power Co.,Ltd.,Changjiang,Hainan,572732,China)

机构地区：[1]南华大学核科学技术学院,湖南衡阳421001 [2]海南核电有限公司,海南昌江572732

出　　处：《核动力工程》2024年第6期185-191,共7页Nuclear Power Engineering

基　　金：国家自然科学基金青年项目(12005096、12305185);湖南省自然科学基金区域联合项目(2023JJ50122);湖南省自然科学基金面上项目(2022JJ30479);2023年度南华大学大学生创新创业训练计划项目(S202310555167)。

摘　　要：核反应堆常规的比例积分(PI)控制器参数整定方法过程繁琐复杂、人为经验依赖性强,难以实现反应堆中多个PI控制器参数的协同优化。为解决这一问题,建立小型压水堆核蒸汽供应控制系统,以反应堆冷却剂平均温度与蒸汽压力控制器参数为优化目标,采用带精英策略的非支配排序遗传算法(NSGA-Ⅱ)实现核蒸汽供应控制系统的参数优化。结果表明,优化后的控制系统有效减少了被控对象的超调量与响应时间,提高了控制系统的控制性能,同时减少了对人为经验的依赖,实现了参数整定过程的智能化。In nuclear reactors,the conventional PI controller parameter tuning method is cumbersome and complex,with strong dependence on human experience,which makes it difficult to achieve the simultaneous co-optimization of multiple PI controller parameters in the reactor.To study this problem,a small pressurised water reactor nuclear steam supply control system is established with the reactor coolant average temperature and steam pressure controller parameters as the optimization objectives,and a Non Dominated Sorting Genetic Algorithm-II(NSGA-Ⅱ)is used to achieve the parameter optimization of the nuclear steam supply control system.The results show that the optimized control system effectively reduces the overshoot and response time of the controlled objects,improves the control performance of the control system,and at the same time lessens the dependence on human experience and achieves the intelligence of the parameter tuning process.

关 键 词：小型压水堆核蒸汽供应系统 PI控制器参数 多目标协同优化 非支配排序遗传算法(NSGA-Ⅱ) 

分 类 号：TL361[核科学技术—核技术及应用]