摘要
随着数字控制技术的发展,核电机组中基于模拟量的传统仪控系统逐步被全数字化技术代替,采用更复杂高效的先进控制技术成为了可能。目前虽然已有采用先进控制算法提升压水堆电厂控制系统性能的研究,但大多只关注控制系统本身而未能充分考虑多个控制系统之间的耦合。为了从顶层协调多个控制系统提升整体控制性能,本文提出了基于粒子群优化的压水堆控制系统设定值决策方法,构建了设定值优化所需的决策目标函数及决策优化运行约束条件,建立的智能决策系统基于压水堆实际运行过程进行设定值离线优化,根据运行工况进行在线智能决策,为底层控制系统提供控制目标的方向和幅度。随后以压水堆核电厂运行中的典型过程为例进行了仿真实验,并与稳态运行时的传统设定值方案进行对比,结果显示:基于粒子群优化的设定值决策方法获得的冷却剂平均温度、稳压器液位、稳压器压力和蒸汽发生器液位的ITSE(Integral of Time multiplied by the Square Error)指标分别降低了58.9%、67.7%、99.9%和83.3%,峰值指标分别下降了62.4%、3.0%、100%和66.3%。表明本文所提出的智能决策方案可以有效减小系统的ITSE指标和峰值指标,提升了压水堆电厂控制系统的整体控制性能和安全裕量。
[Background]Analog-based instrumentation and control systems in nuclear power plants(NPP)are being progressively supplanted by comprehensive digital technologies,enabling the deployment of sophisticated and efficient advanced control methodologies.Although there are studies on improving the control performance of pressurized water reactor(PWR)NPP control systems by advanced control algorithms,most of them only focus on the control system itself without considering the interconnection and coupling among multiple control systems.[Purpose]This study aims to propose a setpoint decision optimization system for coordinating multiple control systems from the top level to optimize the overall control performances and achieve better task execution results.[Methods]The intelligent decision system for PWR control system was optimized based on particle swarm optimization(PSO)method.Both the decision objective function and operation constraint conditions of the intelligent decision system were proposed.Considering the actual operation of PWR,the setpoint was optimized offline and the intelligent decision operation was performed online according to the operation condition to provide the directions and amplitudes of the control targets for the underlying control systems.Subsequently,the typical operation process of the PWR NPP was taken as an example to carry out the simulation of the designed PSO-based intelligent decision-making system,and the simulation results were compared with that of traditional setpoint decision method in term of Integral of Time multiplied by the Square Error(ITSE).[Results]Compared with the control scheme using traditional setpoints,the ITSE values of average coolant temperature in primary loop,pressurizer fluid level,pressurizer pressure and steam generator fluid level obtained by optimized setpoint are decreased by 58.9%,67.7%,99.9%and 83.3%,respectively.The peak values are decreased by 62.4%,3.0%,100%and 66.3%,respectively.[Conclusions]The simulation results show that the system proposed in this study effectively reduce the ITSE and peak value of the system.The overall control performances and safety margin of the control systems of PWR NPP are improved.
作者
张琦
张贤山
孙培伟
魏新宇
ZHANG Qi;ZHANG Xianshan;SUN Peiwei;WEI Xinyu(School of Nuclear Science and Technology,Xi'an Jiaotong University,Xi'an 710049,China;Beijing Hollysys Industrial Software Co.,Ltd,Beijing 100176,China)
出处
《核技术》
北大核心
2025年第5期186-195,共10页
Nuclear Techniques
基金
国家自然科学基金(No.12075181)资助。
关键词
设定值优化
智能决策
粒子群算法
压水堆
控制系统
Setpoint optimization
Intelligent decision-making
Particle swarm optimization method
Pressurizer Water Reactor
Control system
