基于遗传算法的机组再热回热参数优化  

Optimization of Unit's Reheating and Heating Parameters Based on Genetic Algorithm

作　　者：潘加磊[1] 王培红[1] 

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》2008年第2期89-91,共3页Turbine Technology

基　　金：国家自然科学基金项目(50376011);高等学校博士学科点专项科研基金(20060286033)

摘　　要：再热和回热系统是汽轮机热力系统的基础,对机组经济性有较大的影响。研究包含再热参数优化在内的回热焓升优化分配问题。以几个典型工况下的机组再热压力和抽汽压力为优化参数,构造了适于优化的适应度模型,并在热平衡法的基础上采用遗传算法进行优化。通过算例表明:遗传算法具有很好的收敛性和适应性,能迅速地获得全局最优解,而且便于给出各优化参数(甚至是中间变量)之间的关系,为汽轮机循环的最佳加热分配提供了一种便捷而有效的方法。As the base of thermodynamic system, reheating system and heating system have great influence on economic property of unit. This paper studied optimization distribution problem of heating system, which involved optimization of reheating parameter. With the reheating pressure and extraction pressure in several representative conditions as optimizing parameters, the article established an effective fitness-model. Based on the heat balance, the model had been calculated by means of genetic algorithm. The results demonstrate good convergence and adaptability of hybrid genetic algorithm which could achieve global optimization very soon and shows the relations between the optimum parameters （ even the temp parameters） easily. It can be concluded that GA is a promising method for analyzing and solving the optimum distribution problem of unit＇ s heating.

关 键 词：遗传算法 全局优化 最佳加热分配 

分 类 号：TM621.4[电气工程—电力系统及自动化]