基于DE-INSGA-Ⅱ的联合循环系统性能及参数优化研究  

Research on Performance and Parameter Optimization of Combined Circulation System Based on DE-INSGA-Ⅱ

作　　者：陈永军 黄伟 CHEN Yongjun;HUANG Wei(College of Automation Engineering,Shanghai University of Electric Power,Shanghai 200090,China)

机构地区：[1]上海电力大学自动化工程学院,上海200090

出　　处：《锅炉技术》2024年第1期15-22,共8页Boiler Technology

基　　金：上海市“科技创新行动计划”地方院校能力建设专项项目(19020500700);中国华能集团有限公司重点科技资助项目(CHDKJ19-01-80)。

摘　　要：为了研究联合循环系统长期运行后循环效率最优的热力参数匹配,提出了一种改进优化算法,该算法融合了非线性优化思想,并利用DE(differential evolution algorithm)算法思想改善种群初始分布,同时改进快速非支配排序遗传算法NSGA-Ⅱ(non-dominated sorting genetic algorithm)交叉算子。以底循环效率最大为目标函数结合约束条件,对系统的热力参数匹配进行多目标优化。仿真结果表明:所提的DE-INSGA-Ⅱ算法具有良好分布性和收敛性,搜索能力更强。在底循环效率优化问题上,较传统NSGA-Ⅱ算法提高0.44%,余热锅炉效率提高了0.86%,汽轮机效率提升了0.15%。该研究为联合循环机组运行的热力参数匹配提供了新的参考。In order to study the matching of thermal parameters with optimal cycle efficiency after long-term operation of the combined cycle system,an improved optimization algorithm is proposed,which integrates the idea of nonlinear optimization and uses the idea of DE(differential evolution)algorithm to improve the initial distribution of the population,and at the same time improves the non-dominated sorting genetic algorithm(NSGA-Ⅱ)cross operator.Taking the maximum bottom cycle efficiency as the objective function and the constraint condition,the multi-objective optimization of the thermal parameter matching of the system is carried out.The simulation results show that the proposed DE-INSGA-Ⅱ(differential evolution algorithm-improved NSGA-Ⅱ)algorithm has good distribution,convergence and strong search ability.Compared with the traditional NSGA-Ⅱ algorithm,the bottom cycle efficiency is increased by 0.44%,the efficiency of heat recovery steam generator is increased by 0.86%,and the efficiency of the steam turbine is increased by 0.15%.This study provides a new reference for the operation of combined cycle units in the subsequent thermal parameter matching process.

关 键 词：底循环效率 多目标优化 改进NSGA-Ⅱ 联合循环机组 热力参数 

分 类 号：TM611[电气工程—电力系统及自动化]