摘要
为提高跨流域引水工程受水水库引水有效性,研究了耦合长期径流预报信息的跨流域引水受水水库调度模型。首先选取汛期径流预报信息,采用径流预报概率修正先验概率来描述径流的不确定性,建立了贝叶斯随机动态规划模型(BSDP-LTF)。然后将模型应用于碧流河水库,并与仅考虑径流相关的随机动态规划模型(SDP-I)、仅考虑长期预报信息的随机动态规划模型(SDP-LTF)进行比较。比较结果得出在供水保证率基本一致且不增加调度风险的情况下,BSDP-LTF模型相比SDP-I、SDP-LTF模型,可分别减少引水8.2%、4.1%。表明贝叶斯随机动态规划模型BSDP-LTF有效改进了径流描述,提高了跨流域引水的有效性。
In order to improve the water diversion effectiveness of intake reservoir in inter-basin water diversion pro- ject, the intake reservoir operation model coupling long-term runoff forecast is studied. First, the information of runoff forecast in flood season is employed, and the prior probability is corrected by runoff forecast probability to describe the runoff uncertainty. The stochastic dynamic programming model (BSDP-LTF) is established. Then the model is com- pared with stochastic dynamic programming model considering inflow correlation only (SDP-I) and stochastic dynamic programming model considering long-term forecast only (SDP-LTF) in Biliuhe reservoir. Comparative results show that the water diversion is reduced by 8.2% and 4. 1% for the BSDP-LTF model when compared with SDP-I and SDP-LTF in condition of basically the same water supply reliability and not increasing operation risk. The results indicate that the BSDP-LTF model improves the runoff description effectively, and increases the effectiveness of the inter-basin wa- ter diversion.
出处
《水科学进展》
EI
CAS
CSCD
北大核心
2016年第3期458-466,共9页
Advances in Water Science
基金
重大国际(地区)合作研究项目(51320105010)
国家自然科学基金资助项目(51379027)~~
关键词
长期径流预报
跨流域引水
贝叶斯随机动态规划
long-term inflow forecast
inter-basin water transfer
Bayesian stochastic dynamic programming