摘要
以水电厂机组为单元建立了葛洲坝电站的发电模拟模块,据此采用经模拟退火算法改进的混合遗传算法,建立葛洲坝电站非汛期厂内日优化发电调度模型,并将其应用到葛洲坝电站发电计划编制工作中,实现枯水期厂内发电流量的优化分配.采用2007年4月1日至4月10日实际资料对该模型进行验证与校核,结果表明模型模拟单日平均出力的精度达98.84%.经优化10日最多可新增电量1270×104kW.h.
A new method was presented to make daily operation scheme for Gezhouba Hydropower Plant in non-flood season.This method couples a hybrid genetic algorithm improved by simulated annealing with a precisely simulating model which is able to simulate the power generation process to the extent of each unit.By this method,the optimal allocation of the flow among the available power units are achieved successfully.Using the historical data from April 1 to April 10,2007 to verified this method,results showed that the simulation accuracy of average daily output of power plant was 98.84%,and by optimization the maximum 10 days＇ increased electricity output was up to 12.7×10^4kW·h.
出处
《应用基础与工程科学学报》
EI
CSCD
2010年第3期419-427,共9页
Journal of Basic Science and Engineering
基金
"十一五"国家科技支撑计划"特大型梯级水利水电工程安全及高效运行若干关键技术研究"重点项目(20073338900)第九课题(2008BAB29B09)"三峡-葛洲坝梯级水利枢纽调度技术集成及示范"
关键词
葛洲坝电站
混合遗传算法
模拟退火
优化调度
Gezhouba Hydropower Plant
hybrid genetic algorithm
simulated annealing
optimal operation
