水力发电学报2013，Vol.32Issue(3)：62-65,75,5.
解空间遗传算法在水电站厂内经济运行中的研究
Study on solution-generated genetic algorithm applied to in-plant economical operation of hydropower station
摘要
Abstract
A solution-generated genetic algorithm (SGGA) is proposed for in-plant economical operation of hydropower station.This algorithm adopts a new method for generating initial population that can realize a nonnegative fitness function to avoid the cavitations-vibration mode by imposing load balance constraint and unit output constraint on initial population generation,rather than imposing penalties on fitness function design by traditional genetic algorithm (TGA).And a new perturbation mutation operator is introduced to guarantee a feasible solution to the individual after mutation.This SGGA method of in-plant economical operation was applied to the Three Gorges hydropower station and it was compared with TGA.The solutions for several typical loads show that the new algorithm can ensure normal operation of the units by avoiding cavitationsvibration mode,and it produces excellent solutions under the same environment via avoiding searching in the infeasible solution area.This study also offers a new idea for improving the genetic algorithm in its application to in-plant economical operation of hydropower station.关键词
水电工程/机组运行/解空间生成遗传算法/厂内经济运行Key words
hydropower engineering/ unit operation / solution-generated genetic algorithm / in-plant economical operation分类
建筑与水利引用本文复制引用
郑姣,杨侃,蒋咏,卢修元..解空间遗传算法在水电站厂内经济运行中的研究[J].水力发电学报,2013,32(3):62-65,75,5.基金项目
国家科技支撑计划课题三(2009BAC56B03) （2009BAC56B03）
国家重点基础研究规划项目973项目(2012CB417006) （2012CB417006）
江苏高校优势学科建设工程资金资助(PAPD) （PAPD）
