雅砻江下游梯级水库隐随机联合优化调度函数研究  

Research on ISO Dispatching Function of Cascade Hydropower Plants on Lower Reaches of Yalongjiang River

作　　者：李基栋 黄炜斌[1] 马光文[1] 赵庆绪[1] 

机构地区：[1]四川大学水利水电学院,四川成都610065

出　　处：《水电能源科学》2014年第12期49-53,共5页Water Resources and Power

基　　金：国家重点基础研究发展计划(973计划)项目(2013CB036406-4);国家科技支撑计划项目(2008BAB29B09);国家自然科学基金重点项目(50539140);国家自然科学基金项目(50679098)

摘　　要：针对不确定来水梯级水库优化调度问题,基于隐随机调度函数基本原理,以长系列优化调度结果为依据,建立多元线性回归模型、门限回归模型和BP人工神经网络模型模拟雅砻江下游梯级水库联合调度过程,综合对比各调度函数模拟效果,且与确定来水的优化调度结果做了对比。结果表明,门限回归模型和BP神经网络模型调度函数均能较好地模拟梯级水库运行,可指导梯级电站调度运行。For studying the optimal operation of cascade hydro plants under uncertain inflow condition, based on thelong-term optimal operation results, multiple linear regression model, threshold regression model and BP artificial neuralnetwork model were established to simulate cascade operation functions of lower reaches of the Yalongjiang River accord-ing to the implicit stochastic optimization（ISO） principle. The research comprehensively compared every function＇s effectof supporting the real operation and compared them with long term optimal operation. Threshold regression function andBP artificial neural network function are proved to simulate operation of cascade reservoir, which can provide reference foroperation of cascade plants,

关 键 词：联合优化调度函数 雅砻江下游 多元线性回归 门限回归 BP人工神经网络 

分 类 号：TV741[水利工程—水利水电工程]