摘要
蒸汽运行参数对机组经济性有较大的影响。以机组蒸汽参数优化为研究内容,针对非线性优化目标的特点,提出了采用遗传算法优化的新思路;并对遗传算法的解码方式、适应度函数、选择和变异方式进行了改进,使得参与遗传算法运算的所有个体都是可行解,大大减少了搜索中的无效操作,优化了搜索路径,有效地提高了遗传算法求解的效率和质量。算例表明:改进遗传算法的收敛性更好、适应性更强,能更有效地达到或接近全局最优。
Choice of proper reheat parameters has great influence on economic property of unit.According to the nonlinear characteristic of the object,optimization of stream s parameters by means of GA was proposed in this paper.The decoding mode,fitness function and the mode of selection and mutation were improved,which made all the individual feasible,reduced noneffective operation greatly,optimized search path and enhanced calculation efficiency and quality of GA.The results show that the improved hybrid genetic al...
出处
《江苏电机工程》
2008年第1期8-11,共4页
Jiangsu Electrical Engineering
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)
关键词
蒸汽参数优化
改进遗传算法
优化搜索
optimization of steam s parameters
improved hybrid genetic algorithm
optimization of search path
